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104 results on '"Pierre-André Vuissoz"'

1. Performance Study of an MRI Motion-Compensated Reconstruction Program on Intel CPUs, AMD EPYC CPUs, and NVIDIA GPUs

Author

Mohamed Aziz Zeroual, Karyna Isaieva, Pierre-André Vuissoz, and Freddy Odille

Subjects
magnetic resonance imaging, reconstruction, motion, high-performance computing, parallel processing, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Motion-compensated image reconstruction enables new clinical applications of Magnetic Resonance Imaging (MRI), but it relies on computationally intensive algorithms. This study focuses on the Generalized Reconstruction by Inversion of Coupled Systems (GRICS) program, applied to the reconstruction of 3D images in cases of non-rigid or rigid motion. It uses hybrid parallelization with the MPI (Message Passing Interface) and OpenMP (Open Multi-Processing). For clinical integration, the GRICS needs to efficiently harness the computational resources of compute nodes. We aim to improve the GRICS’s performance without any code modification. This work presents a performance study of GRICS on two CPU architectures: Intel Xeon Gold and AMD EPYC. The roofline model is used to study the software–hardware interaction and quantify the code’s performance. For CPU–GPU comparison purposes, we propose a preliminary MATLAB–GPU implementation of the GRICS’s reconstruction kernel. We establish the roofline model of the kernel on two NVIDIA GPU architectures: Quadro RTX 5000 and A100. After the performance study, we propose some optimization patterns for the code’s execution on CPUs, first considering only the OpenMP implementation using thread binding and affinity and appropriate architecture-compilation flags and then looking for the optimal combination of MPI processes and OpenMP threads in the case of the hybrid MPI–OpenMP implementation. The results show that the GRICS performed well on the AMD EPYC CPUs, with an architectural efficiency of 52%. The kernel’s execution was fast on the NVIDIA A100 GPU, but the roofline model reported low architectural efficiency and utilization.

Published
2024
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2. Super-Resolved Dynamic 3D Reconstruction of the Vocal Tract during Natural Speech

Author

Karyna Isaieva, Freddy Odille, Yves Laprie, Guillaume Drouot, Jacques Felblinger, and Pierre-André Vuissoz

Subjects
magnetic resonance imaging, super-resolution, vocal tract, dynamic MRI, speech, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95
Abstract

MRI is the gold standard modality for speech imaging. However, it remains relatively slow, which complicates imaging of fast movements. Thus, an MRI of the vocal tract is often performed in 2D. While 3D MRI provides more information, the quality of such images is often insufficient. The goal of this study was to test the applicability of super-resolution algorithms for dynamic vocal tract MRI. In total, 25 sagittal slices of 8 mm with an in-plane resolution of 1.6 × 1.6 mm2 were acquired consecutively using a highly-undersampled radial 2D FLASH sequence. The volunteers were reading a text in French with two different protocols. The slices were aligned using the simultaneously recorded sound. The super-resolution strategy was used to reconstruct 1.6 × 1.6 × 1.6 mm3 isotropic volumes. The resulting images were less sharp than the native 2D images but demonstrated a higher signal-to-noise ratio. It was also shown that the super-resolution allows for eliminating inconsistencies leading to regular transitions between the slices. Additionally, it was demonstrated that using visual stimuli and shorter text fragments improves the inter-slice consistency and the super-resolved image sharpness. Therefore, with a correct speech task choice, the proposed method allows for the reconstruction of high-quality dynamic 3D volumes of the vocal tract during natural speech.

Published
2023
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3. Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers

Author

Karyna Isaieva, Yves Laprie, Justine Leclère, Ioannis K. Douros, Jacques Felblinger, and Pierre-André Vuissoz

Subjects
Science
Abstract

Measurement(s) Vocal tract images • Speech Technology Type(s) Magnetic Resonance Imaging • Microphone Device Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.16404453

Published
2021
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4. Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach

Author

Karyna Isaieva, Yves Laprie, Nicolas Turpault, Alexis Houssard, Jacques Felblinger, and Pierre-André Vuissoz

Subjects
Electronic computers. Computer science, QA75.5-76.95, Cybernetics, Q300-390
Abstract

Tongue contour extraction from real-time magnetic resonance images is a nontrivial task due to the presence of artifacts manifesting in form of blurring or ghostly contours. In this work, we present results of automatic tongue delineation achieved by means of U-Net auto-encoder convolutional neural network. We present both intra- and inter-subject validation. We used real-time magnetic resonance images and manually annotated 1-pixel wide contours as inputs. Predicted probability maps were post-processed in order to obtain 1-pixel wide tongue contours. The results are very good and slightly outperform published results on automatic tongue segmentation.

Published
2020
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5. 3D Dynamic Spatiotemporal Atlas of the Vocal Tract during Consonant–Vowel Production from 2D Real Time MRI

Author

Ioannis K. Douros, Yu Xie, Chrysanthi Dourou, Karyna Isaieva, Pierre-André Vuissoz, Jacques Felblinger, and Yves Laprie

Subjects
spatiotemporal atlas, generic speaker model, adaptive gaussian kernel, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95
Abstract

In this work, we address the problem of creating a 3D dynamic atlas of the vocal tract that captures the dynamics of the articulators in all three dimensions in order to create a global speaker model independent of speaker-specific characteristics. The core steps of the proposed method are the temporal alignment of the real-time MR images acquired in several sagittal planes and their combination with adaptive kernel regression. As a preprocessing step, a reference space was created to be used in order to remove anatomical information of the speakers and keep only the variability in speech production for the construction of the atlas. The adaptive kernel regression makes the choice of atlas time points independently of the time points of the frames that are used as an input for the construction. The evaluation of this atlas construction method was made by mapping two new speakers to the atlas and by checking how similar the resulting mapped images are. The use of the atlas helps in reducing subject variability. The results show that the use of the proposed atlas can capture the dynamic behavior of the articulators and is able to generalize the speech production process by creating a universal-speaker reference space.

Published
2022
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6. Measurement of Tongue Tip Velocity from Real-Time MRI and Phase-Contrast Cine-MRI in Consonant Production

Author

Karyna Isaieva, Yves Laprie, Freddy Odille, Ioannis K. Douros, Jacques Felblinger, and Pierre-André Vuissoz

Subjects
velocity measurement, magnetic resonance imaging, articulatory motion, phase-contrast MRI, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95
Abstract

We evaluate velocity of the tongue tip with magnetic resonance imaging (MRI) using two independent approaches. The first one consists in acquisition with a real-time technique in the mid-sagittal plane. Tracking of the tongue tip manually and with a computer vision method allows its trajectory to be found and the velocity to be calculated as the derivative of the coordinate. We also propose to use another approach—phase contrast MRI—which enables velocities of the moving tissues to be measured directly. We recorded the sound simultaneously with the MR acquisition which enabled us to make conclusions regarding the relation between the movements and the sound. We acquired the data from two French-speaking subjects articulating /tata/. The results of both methods are in qualitative agreement and are consistent with other reviewer techniques used for evaluation of the tongue tip velocity.

Published
2020
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7. Accuracy of subject-specific prediction of end-systolic time in MRI across a range of RR intervals.

Author

Christophe Meyer, Jacques Felblinger, Pierre-André Vuissoz, and Laurent Bonnemains

Subjects
Medicine, Science
Abstract

BACKGROUND:Prediction of End-Systole time is of utmost importance for cardiac MRI to correctly associate acquired k-space lines during reconstruction of cine acquisitions. This prediction is usually based on the patient's heart rate using Weissler's formula, which was calibrated by linear regression within a population and cannot account for individual variability. OBJECTIVE:We propose an automatic method to build a personalized model that better predicts end-systole. METHODS:A phase contrast sequence was modified to acquire only central k-space line with 6.6ms temporal resolution, in a slice passing through the aorta during 128 heartbeats in 35 subjects. Segmentation of aorta and detection of end of systolic ejection was automatic. Duration of electromechanical systole duration as function of heart rate was determined for each subject separately. RESULTS:In comparison with the global models, the adapted cardiac model predicted significantly better both echocardiographic end-systolic reference (bias = 0ms vs 17ms, p

Published
2017
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8. Is High Temporal Resolution Achievable for Paediatric Cardiac Acquisitions during Several Heart Beats? Illustration with Cardiac Phase Contrast Cine-MRI.

Author

Laurent Bonnemains, Freddy Odille, Christophe Meyer, Gabriella Hossu, Jacques Felblinger, and Pierre-André Vuissoz

Subjects
Medicine, Science
Abstract

During paediatric cardiac Cine-MRI, data acquired during cycles of different lengths must be combined. Most of the time, Feinstein's model is used to project multiple cardiac cycles of variable lengths into a mean cycle.To assess the effect of Feinstein projection on temporal resolution of Cine-MRI.1/The temporal errors during Feinstein's projection were computed in 306 cardiac cycles fully characterized by tissue Doppler imaging with 6-phase analysis (from a population of 7 children and young adults). 2/The effects of these temporal errors on tissue velocities were assessed by simulating typical tissue phase mapping acquisitions and reconstructions. 3/Myocardial velocities curves, extracted from high-resolution phase-contrast cine images, were compared for the 6 volunteers with lowest and highest heart rate variability, within a population of 36 young adults.1/The mean of temporal misalignments was 30 ms over the cardiac cycle but reached 60 ms during early diastole. 2/During phase contrast MRI simulation, early diastole velocity peaks were diminished by 6.1 cm/s leading to virtual disappearance of isovolumic relaxation peaks. 3/The smoothing and erasing of isovolumic relaxation peaks was confirmed on tissue phase mapping velocity curves, between subjects with low and high heart rate variability (p = 0.05).Feinstein cardiac model creates temporal misalignments that impair high temporal resolution phase contrast cine imaging when beat-to-beat heart rate is changing.

Published
2015
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9. Dose-response of superparamagnetic iron oxide labeling on mesenchymal stem cells chondrogenic differentiation: a multi-scale in vitro study.

Author

Emilie Roeder, Christel Henrionnet, Jean Christophe Goebel, Nicolas Gambier, Olivier Beuf, Denis Grenier, Bailiang Chen, Pierre-André Vuissoz, Pierre Gillet, and Astrid Pinzano

Subjects
Medicine, Science
Abstract

AimThe aim of this work was the development of successful cell therapy techniques for cartilage engineering. This will depend on the ability to monitor non-invasively transplanted cells, especially mesenchymal stem cells (MSCs) that are promising candidates to regenerate damaged tissues.MethodsMSCs were labeled with superparamagnetic iron oxide particles (SPIO). We examined the effects of long-term labeling, possible toxicological consequences and the possible influence of progressive concentrations of SPIO on chondrogenic differentiation capacity.ResultsNo influence of various SPIO concentrations was noted on human bone marrow MSC viability or proliferation. We demonstrated long-term (4 weeks) in vitro retention of SPIO by human bone marrow MSCs seeded in collagenic sponges under TGF-β1 chondrogenic conditions, detectable by Magnetic Resonance Imaging (MRI) and histology. Chondrogenic differentiation was demonstrated by molecular and histological analysis of labeled and unlabeled cells. Chondrogenic gene expression (COL2A2, ACAN, SOX9, COL10, COMP) was significantly altered in a dose-dependent manner in labeled cells, as were GAG and type II collagen staining. As expected, SPIO induced a dramatic decrease of MRI T2 values of sponges at 7T and 3T, even at low concentrations.ConclusionsThis study clearly demonstrates (1) long-term in vitro MSC traceability using SPIO and MRI and (2) a deleterious dose-dependence of SPIO on TGF-β1 driven chondrogenesis in collagen sponges. Low concentrations (12.5-25 µg Fe/mL) seem the best compromise to optimize both chondrogenesis and MRI labeling.

Published
2014
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26. A hardware and software system for MRI applications requiring external device data

Author

Karyna Isaieva, Marc Fauvel, Nicolas Weber, Pierre‐André Vuissoz, Jacques Felblinger, Julien Oster, Freddy Odille, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre d'Investigation Clinique - Innovation Technologique [Nancy] (CIC-IT), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), ANR-15-RHUS-0004,FIGHT-HF,Combattre l'insuffisance cardiaque(2015), ANR-17-CE19-0022,Bracoil,Antenne adaptée pour l'IRM mammaire(2017), ANR-20-CE23-0008,Full3DTalkingHead,Tête parlante 3D complète avec simulations aéro-acoustiques(2020), ANR-19-ECVD-0004,MEIDIC-VTACH,Mobile Electro-Imaging for the preDICtion of Ventricular TACHyarrhythmia(2019), Isaieva, Karyna, Combattre l'insuffisance cardiaque - - FIGHT-HF2015 - ANR-15-RHUS-0004 - RHUS - VALID, Antenne adaptée pour l'IRM mammaire - - Bracoil2017 - ANR-17-CE19-0022 - AAPG2017 - VALID, Tête parlante 3D complète avec simulations aéro-acoustiques - - Full3DTalkingHead2020 - ANR-20-CE23-0008 - AAPG2020 - VALID, Mobile Electro-Imaging for the preDICtion of Ventricular TACHyarrhythmia - - MEIDIC-VTACH2019 - ANR-19-ECVD-0004 - ERA-CVD - VALID, and Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Signal processing, Motion, [SPI]Engineering Sciences [physics], Hardware, Computer Systems, [SPI] Engineering Sciences [physics], Respiration, Physiological data, Humans, Radiology, Nuclear Medicine and imaging, Magnetic Resonance Imaging, Real-time, Software
Abstract

International audience; installation which might be impossible in some cases (e.g. pregnant women in lateral position, utilization of a tight flexible coil), and allows monitoring of only respiratory and heart activities. Moreover, being designed for clinical use, they offer no control over data acquisition and post-processing, which can be critical for some applications. For example, standard ECG processing can lead to incorrect QRS detection in case of steep gradient waveforms; no control over respiratory belt signal gain and offset (to avoid signal saturation) is available. Thus, often, accessory devices are thirdparty systems, which offer more flexibility, however have no communication interface with the MR system, or limited ones. Dedicated computer and electronics systems, as well as communication interfaces, are needed for use in either realtime/online applications or retrospective/offline applications. In the following we review several exemplary applications with the aim to derive typical requirements for such systems. Example applications that require real-time processing and communication include ECG denoising (7-10) and detection of the QRS complex (11-13), in order to trigger the MR sequence to the heart rate prospectively. The trigger is provided to the MR system by a TTL signal. The delays introduced by the real-time processing system, as defined by the latency (mean delay) and jitter (standard deviation of the delay), should be significantly lower that the temporal resolution of cardiac MR imaging, which is typically above 20 ms. Real-time display of the denoised ECG is also desired during anesthesia, cardiac stress MRI, or interventional MRI. Prospective motion correction (14) using external devices also relies on a real-time setup to modulate the MRI pulses (RF and magnetic field gradient pulses) in order to compensate for the effect of patient motion during spatial encoding. Low latency is also desired, ideally to be equal to the repetition time (TR) of the sequence or lower, i.e. 3 to 5 ms, though in practice it is limited by the time needed to process video images, e.g. 60 to 150 ms in (15). Software communication interfaces need to be defined with the vendor-dependent pulse sequence program in order to provide certain motion parameters (e.g. translations, rotations).

Published
2022
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29. Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers

Author

Ioannis Douros, Yves Laprie, Pierre-André Vuissoz, Jacques Felblinger, Karyna Isaieva, Justine Leclere, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Centre Hospitalier Universitaire de Reims (CHU Reims), Centre d'Investigation Clinique - Innovation Technologique [Nancy] (CIC-IT), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Isaieva, Karyna

Subjects
Adult, Male, Statistics and Probability, Data Descriptor, Oral anatomy, Speech production, Computer science, Science, Speech recognition, Context (language use), Library and Information Sciences, 01 natural sciences, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], 030218 nuclear medicine & medical imaging, Education, Young Adult, 03 medical and health sciences, Imaging, Three-Dimensional, 0302 clinical medicine, Vocal tract images, 0103 physical sciences, Humans, Speech, Segmentation, Articulatory gestures, 010301 acoustics, Language, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Communication, Middle Aged, Magnetic Resonance Imaging, Computer Science Applications, Metadata, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Female, [SDV.IB]Life Sciences [q-bio]/Bioengineering, France, Statistics, Probability and Uncertainty, Mr images, Articulation (phonetics), Vocal tract, Information Systems
Abstract

The study of articulatory gestures has a wide spectrum of applications, notably in speech production and recognition. Sets of phonemes, as well as their articulation, are language-specific; however, existing MRI databases mostly include English speakers. In our present work, we introduce a dataset acquired with MRI from 10 healthy native French speakers. A corpus consisting of synthetic sentences was used to ensure a good coverage of the French phonetic context. A real-time MRI technology with temporal resolution of 20 ms was used to acquire vocal tract images of the participants speaking. The sound was recorded simultaneously with MRI, denoised and temporally aligned with the images. The speech was transcribed to obtain phoneme-wise segmentation of sound. We also acquired static 3D MR images for a wide list of French phonemes. In addition, we include annotations of spontaneous swallowing., Measurement(s)Vocal tract images • SpeechTechnology Type(s)Magnetic Resonance Imaging • Microphone DeviceSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16404453

Published
2021
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30. Towards the prediction of the vocal tract shape from the sequence of phonemes to be articulated

Author

Karyna Isaieva, Pierre-André Vuissoz, Yves Laprie, Justine Leclere, Vinicius Ribeiro, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Souza Ribeiro, Vinicius de Paulo

Subjects
Speech production, Generalization, Computer science, speech production, Speech recognition, Articulator, 020206 networking & telecommunications, 02 engineering and technology, [INFO] Computer Science [cs], neural networks, Euclidean distance, 030507 speech-language pathology & audiology, 03 medical and health sciences, Position (vector), Data efficiency, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], 0305 other medical science, Set (psychology), phoneme-to-articulatory, Vocal tract
Abstract

International audience; In this work, we address the prediction of speech articulators' temporal geometric position from the sequence of phonemes to be articulated. We start from a set of real-time MRI sequences uttered by a female French speaker. The contours of five articulators were tracked automatically in each of the frames in the MRI video. Then, we explore the capacity of a bidirectional GRU to correctly predict each articulator's shape and position given the sequence of phonemes and their duration. We propose a 5-fold cross-validation experiment to evaluate the generalization capacity of the model. In a second experiment, we evaluate our model's data efficiency by reducing training data. We evaluate the point-to-point Euclidean distance and the Pearson's correlations along time between the predicted and the target shapes. We also evaluate produced shapes of the critical articulators of specific phonemes. We show that our model can achieve good results with minimal data, producing very realistic vocal tract shapes.

Published
2021
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31. Editorial for 'Myocardial Deformation Assessed by MR Feature Tracking in Groups of Patients With Ischemic Heart Disease'

Author

Pierre-André Vuissoz, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)

Subjects
medicine.medical_specialty, business.industry, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Heart Ventricles, Myocardium, Myocardial Ischemia, Magnetic Resonance Imaging, Cine, Heart, Disease, 030204 cardiovascular system & hematology, Deformation (meteorology), 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Text mining, Internal medicine, medicine, Cardiology, Feature tracking, Humans, Radiology, Nuclear Medicine and imaging, business, Ischemic heart, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021
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32. MRI Vocal Tract Sagittal Slices Estimation during Speech Production of CV

Author

Chrysanthi Dourou, Jacques Felblinger, Ajinkya Kulkarni, Pierre-André Vuissoz, Yu Xie, Yves Laprie, Karyna Isaieva, Ioannis Douros, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Department of Neurology, Wuhan University [China], School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)

Subjects
Speech production, Signal processing, speech resources enrichment, Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Speech recognition, 020206 networking & telecommunications, 02 engineering and technology, Sagittal plane, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], Set (abstract data type), RtMRI data, medicine.anatomical_structure, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], vocal tract, 0202 electrical engineering, electronic engineering, information engineering, medicine, Frame (artificial intelligence), 020201 artificial intelligence & image processing, Image transformation, Vocal tract
Abstract

International audience; In this paper we propose an algorithm for estimating vocal tract para sagittal slices in order to have a better overview of the behaviour of the articulators during speech production. The first step is to align the consonant-vowel (CV) data of the sagittal plains between them for the train speaker. Sets of transformations that connect the midsagittal frames with the neighbouring ones is acquired for the train speaker. Another set of transformations is calculated which transforms the midsagittal frames of the train speaker to the corresponding midsagittal frames of the test speaker and is used to adapt to the test speaker domain the previously computed sets of transformations. The newly adapted transformations are applied to the midsagittal frames of the test speaker in order to estimate the neighbouring sagittal frames. Several mono speaker models are combined to produce the final frame estimation. To evaluate the results, image cross-correlation between the original and the estimated frames was used. Results show good agreement between the original and the estimated frames.

Published
2021
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33. Synthesize MRI vocal tract data during CV production

Author

Ioannis Douros, Chrysanthi Dourou, Yu Xie, jacques Felblinger, Karyna Isaieva, Pierre-André Vuissoz, Yves Laprie, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Department of Neurology, Wuhan University [China], Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Laprie, Yves

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Abstract

International audience; A set of rtMR image transformations across time is computed during the production of CV that is afterwards applied to a new speaker in order to synthesize his/her CV pseudo rtMRI data. Synthesized images are compared with the original ones using image cross-correlation. 2 Purpose To be able to enlarge MRI speech corpus by synthesizing data.

Published
2020

34. Vocal tract sagittal slices estimation from MRI midsagittal slices during speech production of CV

Author

Ioannis Douros, Yu Xie, Chrysanthi Dourou, jacques Felblinger, Karyna Isaieva, Pierre-André Vuissoz, Yves Laprie, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Department of Neurology, Wuhan University [China], School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Laprie, Yves, Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Abstract

International audience

Published
2020

35. Automatic Tongue Delineation from MRI Images with a Convolutional Neural Network Approach

Author

Alexis Houssard, Yves Laprie, Jacques Felblinger, Pierre-André Vuissoz, Nicolas Turpault, Karyna Isaieva, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Centre d'Investigation Clinique - Innovation Technologique [Nancy] (CIC-IT), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)

Subjects
0209 industrial biotechnology, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Convolutional neural network, Task (project management), Mri image, 020901 industrial engineering & automation, Artificial Intelligence, Tongue, 0202 electrical engineering, electronic engineering, information engineering, medicine, Computer vision, [INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS, ComputingMethodologies_COMPUTERGRAPHICS, medicine.diagnostic_test, business.industry, Magnetic resonance imaging, medicine.anatomical_structure, Computer Science::Computer Vision and Pattern Recognition, 020201 artificial intelligence & image processing, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; Tongue contour extraction from real-time magnetic resonance images is a nontrivial task due to the presence of artifacts manifesting in form of blurring or ghostly contours. In this work, we present results of automatic tongue delineation achieved by means of U-Net auto-encoder convolutional neural network. We present both intra- and inter-subject validation. We used real-time magnetic resonance images and manually annotated 1-pixel wide contours as inputs. Predicted probability maps were post-processed in order to obtain 1-pixel wide tongue contours. The results are very good and slightly outperform published results on automatic tongue segmentation.

Published
2020
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36. Coupled transfer function model for the evaluation of implanted cables safety in MRI

Author

Pierre-André Vuissoz, Julie Kabil, Jacques Felblinger, Alexia Missoffe, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'investigation clinique [Nancy] (CIC), and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)

Subjects
Work (thermodynamics), Scanner, Materials science, Hot Temperature, Phantoms, Imaging, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Temperature, Mechanics, Transfer function, Magnetic Resonance Imaging, 030218 nuclear medicine & medical imaging, Electrodes, Implanted, 03 medical and health sciences, Coupling (physics), 0302 clinical medicine, Transfer function model, Electrode, Radiology, Nuclear Medicine and imaging, Additive model, Constant (mathematics), [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery
Abstract

International audience; PurposeMultiple medical‐device leads implanted next to each other are often encountered in clinical practice. The aim of this work is to study a coupled transfer function model to evaluate the safety of these coupled leads submitted to the RF field of a 1.5T MRI scanner for a constant distance between both leads.MethodsThe effect of coupling on the heating of 2 cables with different termination conditions is evaluated experimentally. The coupled and single transfer functions are determined experimentally and used to predict the relative temperature increases of both cables alone and coupled. Two different coupled models, an additive model and a global model, are proposed. The coupled transfer functions are also simulated.ResultsThe coupling between cables has a strong influence on the resulting heating at the electrodes. The coupled additive transfer function model is a relevant tool to evaluate the heating of coupled leads separated by a constant distance. The global model underestimates the heating in one of the coupled cases by about 30%. The measured coupled transfer functions coincide with the simulated models.ConclusionIt is necessary to take into account the coupling effect between leads to evaluate the safety of implanted devices. This work shows that, in the case of 2 cables separated by a constant distance, that an experimentally determined coupled transfer function allows estimation of the heating of the 2 electrodes for a given incident field. Further work should take into account the in vivo varying distance between the 2 cables.

Published
2020
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37. Calibration and non-orthogonality correction of three-axis Hall sensors for the monitoring of MRI workers' exposure to static magnetic fields

Author

Cédric Pasquier, Lamia Belguerras, Nicolas Weber, Freddy Odille, Pierre-André Vuissoz, Jacques Felblinger, and Antoine Delmas

Subjects
Electromagnetic field, Physics, Scanner, Physiology, Acoustics, 0206 medical engineering, Biophysics, 02 engineering and technology, General Medicine, EMF measurement, 020601 biomedical engineering, 030218 nuclear medicine & medical imaging, Magnetic field, 03 medical and health sciences, 0302 clinical medicine, Radiology, Nuclear Medicine and imaging, Hall effect sensor, Orthogonalization, Bioelectromagnetics, Voltage
Abstract

A Magnetic Resonance Imaging (MRI) scanner uses three different electromagnetic fields (EMF) to produce body images: a static permanent magnetic field (MF), several pulsed magnetic gradients, and a radiofrequency pulse. As a result, any occupation that includes an MRI exposes workers to a strong MF. The World Health Organization has now given the monitoring of occupational EMF exposure a high priority. One design for a low-cost, compact MF exposure monitor (« MR exposimeter ») uses a set of three orthogonally assembled Hall sensors. However, at such a strong EMF exposure intensity, the non-linearity and non-orthogonality (misalignment between the three Hall sensors) have an impact on the accuracy of EMF measurement. Therefore, a sensor characterization was performed in order to link Hall-effect output voltage to MF intensity. The sensor was then calibrated using an orthogonalization matrix and an offset vector. For each sensor configuration, the matrix and vector parameters were optimized with a calibration set generated by the movement of a three-axis sensor inside homogeneous MF areas. Once calibrated, the sensor was tested at different MF intensities and returned accuracy improvements. This calibration procedure was tested on synthetic data and performed on experimental data. The calibration parameters can be easily reused by the user, and their stability could be used as a quality control sensor. Finally, real-time monitoring test for static MF exposure was completed and validated on an MRI worker during a typical working day. Bioelectromagnetics. 39:108-119, 2018. © 2018 Wiley Periodicals, Inc.

Published
2018
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38. Décret no2016–1074 relatif à la protection des travailleurs contre les risques dus aux champs électromagnétiques

Author

Cédric Pasquier, Pierre-André Vuissoz, D. Vetter, J. Felblinger, A. Delmas, and C. Dessale

Subjects
03 medical and health sciences, 0302 clinical medicine, Nuclear Energy and Engineering, Renewable Energy, Sustainability and the Environment, Health, Toxicology and Mutagenesis, Public Health, Environmental and Occupational Health, Safety, Risk, Reliability and Quality, Waste Management and Disposal, 030217 neurology & neurosurgery, 030218 nuclear medicine & medical imaging
Abstract

Sorti le 3 aout 2016 et applicable au premier janvier 2017, le decret 2016–1074 etablit des regles et recommandations a suivre pour proteger les travailleurs face aux risques dus aux champs electromagnetiques. Transposant la directive europeenne 2013/35/UE, il concerne tout employeur et impose au minimum l'etablissement d'une evaluation des risques. Les unites, clinique ou de recherche, utilisant des dispositifs d'imagerie par resonance magnetique (IRM) sont particulierement concernees. En effet, cette modalite d'imagerie emet des champs electromagnetiques susceptibles d'engendrer des niveaux d'exposition des travailleurs depassant les valeurs declenchant l'action et les valeurs limites d'exposition definies par la directive et le decret. Une section de ce dernier lui est d'ailleurs entierement consacree. Le present document propose, en premier lieu, une analyse detaillee du decret 2016–1074 et des obligations de l'employeur. Il propose, dans un second temps, une analyse concernant la mise en application de cette directive et du decret associe pour le dispositif particulier qu'est l'IRM.

Published
2017
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39. MRI ‘EXPOSIMETRY’: HOW TO ANALYZE, COMPARE AND REPRESENT WORKER EXPOSURE TO STATIC MAGNETIC FIELD?

Author

Jacques Felblinger, Nicolas Weber, Joris Piffre, Cédric Pasquier, Pierre-André Vuissoz, Antoine Delmas, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Service de neurologie [CHRU Nancy], Département de Radiologie adultes [CHRU Nancy], and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Université de Lorraine (UL)

Subjects
Electromagnetic field, Quality control charts, Computer science, 030218 nuclear medicine & medical imaging, Emf exposure, 03 medical and health sciences, Electromagnetic Fields, Radiation Protection, 0302 clinical medicine, Nuclear magnetic resonance, Radiation Monitoring, Occupational Exposure, Humans, Radiology, Nuclear Medicine and imaging, Simulation, Radiation, Radiological and Ultrasound Technology, Magnetic field exposure, Public Health, Environmental and Occupational Health, General Medicine, Magnetostatics, Magnetic Resonance Imaging, Europe, [SDV.IB]Life Sciences [q-bio]/Bioengineering, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 030217 neurology & neurosurgery
Abstract

International audience; Worker exposure to electromagnetic fields (EMF) is a growing concern of international commissions. A European directive from 2013 (2013/35/EU) recommend to estimate or measure EMF exposure of all exposed workers. Magnetic resonance imaging (MRI) workers are specially concerned by this point because they work all day long in the vicinity of a very strong magnet (generally 1.5 or 3 T), which cannot be turned off. Setting up a magnetic field monitoring device on these workers would therefore be a good way to ensure their security. European directive threshold adequacy could then be verified. But this verification does not ensure a complete analysis of the worker exposure. Such an analysis based on quality control charts and exposure time's metrics has been described in this paper. The proposed magnetic field exposure analysis has additionally been tested on a long-term exposure follow-up of 18 MRI workers during 2 months.

Published
2017
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40. Using Silence MR Image to Synthesise Dynamic MRI Vocal Tract Data of CV

Author

Chrysanthi Dourou, Pierre-André Vuissoz, Karyna Isaieva, Yu Xie, Jacques Felblinger, Ioannis Douros, Ajinkya Kulkarni, Yves Laprie, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Department of Neurology, Wuhan University [China], Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Speech recognition, Frame (networking), 020206 networking & telecommunications, 02 engineering and technology, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], Image (mathematics), Set (abstract data type), Silence, 030507 speech-language pathology & audiology, 03 medical and health sciences, image transformation, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], vocal tract, Dynamic contrast-enhanced MRI, 0202 electrical engineering, electronic engineering, information engineering, Mr images, 0305 other medical science, Speech resources enrichment, Vocal tract, rtMRI data, pseudo rtMRI synthesis
Abstract

International audience; In this work we present an algorithm for synthesising pseudo rtMRI data of the vocal tract. rtMRI data on the midsagittal plane were used to synthesise target consonant-vowel (CV) using only a silence frame of the target speaker. For this purpose, several single speaker models were created. The input of the algorithm is a silence frame of both train and target speaker and the rtMRI data of the target CV. An image transformation is computed from each CV frame to the next one, creating a set of transformations that describe the dynamics of the CV production. Another image transformation is computed from the silence frame of train speaker to the silence frame of the target speaker and is used to adapt the set of transformations computed previously to the target speaker. The adapted set of transformations is applied to the silence of the target speaker tosynthesise his/her CV pseudo rtMRI data. Synthesised images from multiple single speaker models are frame aligned and then averaged to create the final version of synthesised images. Synthesised images are compared with the original ones using image cross-correlation. Results show good agreement between the synthesised and the original images.

Published
2020

41. Broadband electrocardiogram acquisition for improved suppression of MRI gradient artifacts

Author

Pierre-André Vuissoz, André Guillou, Freddy Odille, Jacques Felblinger, Jesús E Dos Reis, Julien Oster, Gregory Petitmangin, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'Investigation Clinique - Innovation Technologique [Nancy] (CIC-IT), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), and Schiller Médical SAS

Subjects
Scanner, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Physiology, Computer science, 0206 medical engineering, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Biomedical Engineering, Biophysics, Image processing, 02 engineering and technology, 030218 nuclear medicine & medical imaging, Electrocardiography, 03 medical and health sciences, QRS complex, 0302 clinical medicine, Software, Physiology (medical), Image Processing, Computer-Assisted, medicine, Humans, Computer vision, Signal processing, medicine.diagnostic_test, business.industry, Bandwidth (signal processing), Signal Processing, Computer-Assisted, Magnetic resonance imaging, Magnetic Resonance Imaging, 020601 biomedical engineering, Artificial intelligence, Artifacts, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Blanking
Abstract

International audience; Objective: Despite being routinely acquired during MRI examinations for triggering or monitoring purposes, electrocardiogram (ECG) signal recording and analysis remain challenging due to the inherent magnetic environment of an MRI scanner. The ECG signals are particularly distorted by the induction of electrical fields in the body by the MRI gradients. In this study, we propose a new hardware and software solution for the acquisition of ECG signal during MRI up to 3 T.Approach: Instead of restricting the sensor bandwidth to limit these gradient artifacts, the new sensor architecture has a higher bandwidth, higher sampling frequency and larger input dynamics, in order to acquire the ECG signals and the gradient artifacts more precisely. Signal processing based on a novel detection algorithm and blanking are then applied for improved artifact suppression.Main results: The proposed sensor allows the gradient artifacts to be acquired more precisely, and these artifacts are recorded with peak-to-peak amplitudes two orders of magnitude larger than for QRS complexes. The proposed method outperforms a state-of-the-art approach both in terms of signal quality (+9% 'SNR') and accuracy of QRS detection (+11%).Significance: The proposed hardware and software solutions open the way for the acquisition of high-quality of ECG gating in MRI, and improved diagnostic quality of ECG signals in MRI.

Published
2020
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42. A Multimodal Real-Time MRI Articulatory Corpus of French for Speech Research

Author

Arun A. Joseph, Jens Frahm, Dirk Voit, Yves Laprie, Karyna Isaieva, Freddy Odille, Ioannis Douros, Anastasiia Tsukanova, Jacques Felblinger, Pierre-André Vuissoz, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Biomedizinische NMR Forschungs GmbH [Göttingen], Max-Planck-Institut für Biophysikalische Chemie - Max Planck Institute for Biophysical Chemistry [Göttingen], Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, and Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Larynx, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Speech production, Epiglottis, Computer science, speech production, Speech recognition, 02 engineering and technology, speech syn- thesis, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 030507 speech-language pathology & audiology, 03 medical and health sciences, Tongue, 0202 electrical engineering, electronic engineering, information engineering, medicine, Index Terms: speech corpus, Spontaneous speech, multi-modal database, 020206 networking & telecommunications, Real-time MRI, medicine.anatomical_structure, Duration (music), French language, real-time MRI data, 0305 other medical science, Vocal tract, 3D MRI data
Abstract

International audience; In this work we describe the creation of ArtSpeechMRIfr: a real-time as well as static magnetic resonance imaging (rtMRI, 3D MRI) database of the vocal tract. The database contains also processed data: denoised audio, its phonetically aligned annotation, articulatory contours, and vocal tract volume information , which provides a rich resource for speech research. The database is built on data from two male speakers of French. It covers a number of phonetic contexts in the controlled part, as well as spontaneous speech, 3D MRI scans of sustained vocalic articulations, and of the dental casts of the subjects. The corpus for rtMRI consists of 79 synthetic sentences constructed from a phonetized dictionary that makes possible to shorten the duration of acquisitions while keeping a very good coverage of the phonetic contexts which exist in French. The 3D MRI includes acquisitions for 12 French vowels and 10 consonants, each of which was pronounced in several vocalic contexts. Ar-ticulatory contours (tongue, jaw, epiglottis, larynx, velum, lips) as well as 3D volumes were manually drawn for a part of the images.

Published
2019

43. One‐millimeter isotropic breast diffusion‐weighted imaging: Evaluation of a superresolution strategy in terms of signal‐to‐noise ratio, sharpness and apparent diffusion coefficient

Author

Maya Delbany, Jacques Felblinger, Julie Poujol, Freddy Odille, Aurelien Bustin, Isabelle Thomassin‐Naggara, Pierre-André Vuissoz, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), School of Biomedical Engineering & Imaging Sciences [London], Guy's and St Thomas' Hospital [London]-King‘s College London, Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Université Paris Descartes - Faculté de Médecine (UPD5 Médecine), Université Paris Descartes - Paris 5 (UPD5), Centre d'Investigation Clinique - Innovation Technologique [Nancy] (CIC-IT), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vuissoz, Pierre-André, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)

Subjects
Adult, Databases, Factual, diffusion (rs-EPI), [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Monte Carlo method, Breast Neoplasms, Signal-To-Noise Ratio, 030218 nuclear medicine & medical imaging, Tikhonov regularization, 03 medical and health sciences, Beltrami regularization, 0302 clinical medicine, Optics, Image Processing, Computer-Assisted, Effective diffusion coefficient, Humans, Radiology, Nuclear Medicine and imaging, Breast, breast magnetic resonance imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Physics, business.industry, Echo-Planar Imaging, Isotropy, Middle Aged, Superresolution, Healthy Volunteers, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Diffusion Magnetic Resonance Imaging, Millimeter, Female, business, Monte Carlo Method, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery, Normal breast, superresolution reconstruction, Diffusion MRI
Abstract

International audience; Purpose: To quantitatively evaluate a superresolution technique for 3D, one-millimeter isotropic diffusion-weighted imaging (DWI) of the whole breasts.Methods: Isotropic 3D DWI datasets are obtained using a combination of (i) a readout-segmented diffusion-weighted-echo-planar imaging (DW-EPI) sequence (rs-EPI), providing high in-plane resolution, and (ii) a superresolution (SR) strategy, which consists of acquiring 3 datasets with thick slices (3 mm) and 1-mm shifts in the slice direction, and combining them into a 1 × 1 × 1-mm3 dataset using a dedicated reconstruction. Two SR reconstruction schemes were investigated, based on different regularization schemes: conventional Tikhonov or Beltrami (an edge-preserving constraint). The proposed SR strategy was compared to native 1 × 1 × 1-mm3 acquisitions (i.e. with 1-mm slice thickness) in 8 healthy subjects, in terms of signal-to-noise ratio (SNR) efficiency, using a theoretical framework, Monte Carlo simulations and region-of-interest (ROI) measurements, and image sharpness metrics. Apparent diffusion coefficient (ADC) values in normal breast tissue were also compared.Results: The SR images resulted in an SNR gain above 3 compared to native 1 × 1 × 1-mm3 using the same acquisition duration (acquisition gain 3 and reconstruction gain >1). Beltrami-SR provided the best results in terms of SNR and image sharpness. The ADC values in normal breast measured from Beltrami-SR were preserved compared to low-resolution images (1.91 versus 1.97 ×10-3 mm2 /s, P = .1).Conclusion: A combination of rs-EPI and SR allows 3D, 1-mm isotropic breast DWI data to be obtained with better SNR than a native 1-mm isotropic acquisition. The proposed DWI protocol might be of interest for breast cancer monitoring/screening without injection.

Published
2018
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44. Transmission Line Model of an Implanted Insulated Cable for Magnetic Resonance Imaging Radiofrequency Hazard Evaluation

Author

Julie Kabil, Pierre-André Vuissoz, Alexia Missoffe, Jacques Felblinger, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), and Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Physics, Radiation, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, 020206 networking & telecommunications, 02 engineering and technology, Function (mathematics), Mechanics, Transfer function, Expression (mathematics), 030218 nuclear medicine & medical imaging, Power (physics), 03 medical and health sciences, 0302 clinical medicine, Transmission line, Electrode, 0202 electrical engineering, electronic engineering, information engineering, Radiology, Nuclear Medicine and imaging, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Constant (mathematics), Hazard evaluation, Instrumentation, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; This paper demonstrates that one can model the power deposited at the electrode of an implanted insulated cable submitted to the radiofrequency field of a 1.5 T magnetic resonance imaging modality (64 MHz) with a transmission line model. This offers an alternative that is more related to physics to the usually used transfer function model. The equivalence between the models is shown through a finite difference model and a new analytical formula for the transfer function as a function of transmission line parameters. First, the possibility of modeling an insulated cable with a transmission line model was analyzed through full-wave numerical simulations. The assumption of a transmission line model underlying the transfer function model was shown to be right for a simple cable embedded in tissue imitating gel, and the transmission line parameters extracted from this analysis were consistent with analytical formulas derived from the laws of physics. The transmission line model predictions were first compared to experimental and simulated data of the cable transfer function and then to experimental and simulated data of the resonant behavior as a function of length of cables with different termination conditions. The measured and simulated transfer functions fit perfectly a transmission line model with an analytical expression of the propagating constant. The transmission line model extracted from the transfer function allows us to predict the resonant behavior of two cables with different termination conditions.

Published
2018
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45. Joint Reconstruction of Multiple Images and Motion in MRI: Application to Free-Breathing Myocardial <formula formulatype='inline'><tex Notation='TeX'>${\rm T}_{2}$</tex></formula> Quantification

Author

Pierre-Yves Marie, Freddy Odille, Marine Beaumont, Pierre-André Vuissoz, Anne Menini, Jacques Felblinger, and Jean-Marie Escanye

Subjects
Radiological and Ultrasound Technology, medicine.diagnostic_test, Image quality, Computer science, business.industry, media_common.quotation_subject, Image (category theory), Motion (geometry), Magnetic resonance imaging, Image segmentation, Iterative reconstruction, 030218 nuclear medicine & medical imaging, Computer Science Applications, 03 medical and health sciences, 0302 clinical medicine, medicine, Contrast (vision), Computer vision, Artificial intelligence, Electrical and Electronic Engineering, business, Ghosting, 030217 neurology & neurosurgery, Software, media_common
Abstract

Exploiting redundancies between multiple images of an MRI examination can be formalized as the joint reconstruction of these images. The anatomy is preserved indeed so that specific constraints can be implemented (e.g. most of the features or spatial gradients should be in the same place in all these images) and only the contrast changes from one image to another need to be encoded. The application of this concept is particularly challenging in cardiovascular and body imaging due to the complex organ deformations, especially with the patient breathing. In this study a joint optimization framework is proposed for reconstructing multiple MR images together with a nonrigid motion model. The motion model takes into account both intra-image and inter-image motion and therefore can correct for most ghosting/blurring artifacts and misregistration between images. The framework was validated with free-breathing myocardial ${\rm T}_{2}$ mapping experiments from nine heart transplant patients at 1.5 T. Results showed improved image quality and excellent image alignment with the multi-image reconstruction compared to the independent reconstruction of each image. Segment-wise myocardial ${\rm T}_{2}$ values were in good agreement with the reference values obtained from multiple breath-holds (62.5 $\pm$ 11.1 ms against 62.2 $\pm$ 11.2 ms which was not significant with ${\rm p}=0.49$ ).

Published
2016
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46. Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech

Author

Benjamin Elie, Pierre-André Vuissoz, Anastasiia Tsukanova, Yves Laprie, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Larynx, Articulatory synthesis, Epiglottis, Deformable objects, Computer science, business.industry, Articulator, 020206 networking & telecommunications, 02 engineering and technology, 01 natural sciences, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], medicine.anatomical_structure, Index Terms-Speech, Tongue, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Articulatory models, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, medicine, Computer vision, Artificial intelligence, business, 010301 acoustics, Vocal tract, MRI
Abstract

International audience; This work concerns the construction of articulatory models for synthesis of speech, and more specifically the velum and epiglottis. The direct application of principal component analysis to the contours of these articulators extracted from MRI images results in unrealistic factors due to delineation errors. The approach described in this paper relies on the application of PCA to the centerline of the articulator and a simple reconstruction algorithm to obtain the global articulator contour. The complete articulatory model was constructed from static Magnetic Resonance (MR) images because their quality is much better than that of dynamic MR images. We thus assessed the extent to which the model constructed from static images is capable of approaching the vocal tract shape in MR images recorded at 55 Hz for continuous speech. The analysis of reconstruction errors shows that it is necessary to add dynamic images to the database of static images, in particular to approach the tongue shape for the /l/ sound.

Published
2018

47. Isotropic 3D cardiac cine MRI allows efficient sparse segmentation strategies based on 3D surface reconstruction

Author

Freddy Odille, Aurelien Bustin, Shufang Liu, Bailiang Chen, Laurent Bonnemains, Pierre-André Vuissoz, Jacques Felblinger, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre d'Investigation Clinique - Innovation Technologique [Nancy] (CIC-IT), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), General Electric Global Research Center, Munich, CHU Strasbourg, Vuissoz, Pierre-André, Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), and Technische Universität München [München] (TUM)

Subjects
Adolescent, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Computer science, Magnetic Resonance Imaging, Cine, Standard deviation, 030218 nuclear medicine & medical imaging, Beltrami regularization, 03 medical and health sciences, Magnetic resonance imaging, 0302 clinical medicine, Imaging, Three-Dimensional, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, motion-compensated reconstruction, medicine, Humans, Radiology, Nuclear Medicine and imaging, Segmentation, Computer vision, Child, Cardiac imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, medicine.diagnostic_test, business.industry, Isotropy, Heart, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, super-resolution reconstruction, 3. Good health, Cine mri, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Left ventricular cavity, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery, Surface reconstruction, Algorithms
Abstract

International audience; Purpose: Segmentation of cardiac cine MRI data is routinely used for the volumetric analysis of cardiac function. Conventionally, 2D contours are drawn on short-axis (SAX) image stacks with relatively thick slices (typically 8 mm). Here, an acquisition/reconstruction strategy is used for obtaining isotropic 3D cine datasets; reformatted slices are then used to optimize the manual segmentation workflow.Methods: Isotropic 3D cine datasets were obtained from multiple 2D cine stacks (acquired during free-breathing in SAX and long-axis (LAX) orientations) using nonrigid motion correction (cine-GRICS method) and super-resolution. Several manual segmentation strategies were then compared, including conventional SAX segmentation, LAX segmentation in three views only, and combinations of SAX and LAX slices. An implicit B-spline surface reconstruction algorithm is proposed to reconstruct the left ventricular cavity surface from the sparse set of 2D contours.Results: All tested sparse segmentation strategies were in good agreement, with Dice scores above 0.9 despite using fewer slices (3-6 sparse slices instead of 8-10 contiguous SAX slices). When compared to independent phase-contrast flow measurements, stroke volumes computed from four or six sparse slices had slightly higher precision than conventional SAX segmentation (error standard deviation of 5.4 mL against 6.1 mL) at the cost of slightly lower accuracy (bias of -1.2 mL against 0.2 mL). Functional parameters also showed a trend to improved precision, including end-diastolic volumes, end-systolic volumes, and ejection fractions).Conclusion: The postprocessing workflow of 3D isotropic cardiac imaging strategies can be optimized using sparse segmentation and 3D surface reconstruction. Magn Reson Med 79:2665-2675, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Published
2017
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48. New transmission line model of an insulated cable embedded in gel for MRI radiofrequency interaction hazard evaluation as an alternative to the transfer function model

Author

Alexia Missoffe, Julie Kabil, Pierre-André Vuissoz, jacques Felblinger, Missoffe, Alexia, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Radiologie et Echographie [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Région LorraineFEDER, SpinE, Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)

Subjects
Ligne de transmission, [SPI.ELEC] Engineering Sciences [physics]/Electromagnetism, MRI safety, heating, transmission line, Sécurité IRM, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], pacemaker, [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, radiofrequency, Radiofréquences, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], transfer function, [MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP], [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
Abstract

Object: To demonstrate the possibility to model the power deposited at the electrode of an insulated cable in gel at 64MHz with a transmission line model with a strictly passive electrode model. This offers a more related to physics alternative to the transfer function model. The equivalence between both models is shown.Materials and Methods: In a first step, the possibility of modeling an insulated cable with a transmission line model was analyzed through full-wave numerical simulations. An electrode model that has a physical meaning was proposed. The transmission line model predictions were confronted to experimental and simulated data of the transfer function of a cable and of the resonant behavior as a function of length of cables with different termination conditions.Results: The assumption of a transmission line model which underlies the transfer function model is right for a simple cable embedded in tissue imitating gel. A transmission line model extracted from a transfer function allows to predict the resonant behavior of two cables with different termination conditions.Conclusion: A transmission line model of an insulated cable embedded in tissue imitating gel offers a more directly related to physics alternative to the transfer function model.

Published
2017

49. High spatiotemporal cineMRI films using compressed sensing for acquiring articulatory data

Author

Pierre-André Vuissoz, Yves Laprie, Benjamin Elie, Freddy Odille, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), FEDER et Région Lorraine, Elie, Benjamin, Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Computer science, 02 engineering and technology, Iterative reconstruction, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Compressed Sensing, 0202 electrical engineering, electronic engineering, information engineering, medicine, Computer vision, Image resolution, ComputingMilieux_MISCELLANEOUS, Signal processing, medicine.diagnostic_test, business.industry, Magnetic resonance imaging, Frame rate, Missing data, Dynamic speech MRI, [PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph], Compressed sensing, Line (geometry), 020201 artificial intelligence & image processing, Artificial intelligence, [PHYS.MECA.ACOU] Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph], business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Articulatory data, Vocal tract
Abstract

International audience; The paper presents a method to acquire articulatory data from a sequence of MRI images at a high framerate. The acquisition rate is enhanced by partially collecting data in the kt-space. The combination of compressed sensing technique, along with homodyne reconstruction, enables the missing data to be recovered. The good reconstruction is guaranteed by an appropriate design of the sampling pattern. It is based on a pseudo-random Cartesian scheme, where each line is partially acquired for use of the homodyne reconstruction, and where the lines are pseudo-randomly sampled: central lines are constantly acquired and the sampling density decreases as the lines are far from the center. Application on real speech data show that the framework enables dynamic sequences of vocal tract images to be recovered at a framerate higher than 30 frames per second and with a spatial resolution of 1 mm. A method to extract articulatory data from contour identification is presented. It is intended, in fine, to be used for the creation of a large database of articulatory data.

Published
2016
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50. Free-breathing imaging of the heart using 2D cine-GRICS (generalized reconstruction by inversion of coupled systems) with assessment of ventricular volumes and function

Author

Adnane Benhadid, Pierre-André Vuissoz, Jacques Felblinger, Damien Mandry, Maelene Lohezic, Freddy Odille, Brice Fernandez, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Service d'Imagerie Médicale [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Computer science department [University College London] (UCL-CS), University College of London [London] (UCL), and Vuissoz, Pierre-André

Subjects
Male, Cardiac function curve, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Heart Ventricles, Cardiac-Gated Imaging Techniques, Magnetic Resonance Imaging, Cine, Image processing, 030218 nuclear medicine & medical imaging, Young Adult, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Cardiac magnetic resonance imaging, Sliding window protocol, Image Processing, Computer-Assisted, medicine, Humans, Radiology, Nuclear Medicine and imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Physics, Ejection fraction, medicine.diagnostic_test, Phantoms, Imaging, business.industry, Respiration, Magnetic resonance imaging, Steady-state free precession imaging, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, medicine.anatomical_structure, Ventricle, Linear Models, cardiovascular system, Female, Artifacts, Nuclear medicine, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms, 030217 neurology & neurosurgery
Abstract

Purpose: To assess cardiac function by means of a novel free-breathing cardiac magnetic resonance imaging (MRI) strategy. Materials and Methods: A stack of ungated 2D steady-state free precession (SSFP) slices was acquired during free breathing and reconstructed as cardiac cine imaging based on the generalized reconstruction by inversion of coupled systems (GRICS). A motion-compensated sliding window approach allows reconstructing cine movies with most motion artifacts cancelled. The proposed reconstruction uses prior knowledge from respiratory belts and electrocardiogram recordings and features a piecewise linear model that relates the electrocardiogram signal to cardiac displacements. The free-breathing protocol was validated in six subjects against a standard breath-held protocol. Results: Image sharpness, as assessed by the image gradient entropy, was comparable to that of breath-held images and significantly better than in uncorrected images. Volumetric parameters of cardiac function in the left ventricle (LV) and right ventricle (RV) were similar, including end-systolic volumes, end-diastolic volumes and mass, stroke volumes, and ejection fractions (with differences of 3% ± 2.4 in the LV and 2.9% ± 4.4 in the RV). The duration of the free-breathing protocol was nearly the same as the breath-held protocol. Conclusion: Free-breathing cine-GRICS enables accurate assessment of volumetric parameters of cardiac function with efficient correction of motion. J. Magn. Reson. Imaging 2012;340-351. © 2011 Wiley Periodicals, Inc.

Published
2011
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