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11 results

1. Electron tomography combining ESEM and STEM: A new 3D imaging technique

Author

José Ferreira, Catherine Gauthier, P. Jornsanoh, G. Thollet, Karine Masenelli-Varlot, Agnès Bogner, Matériaux, ingénierie et science [Villeurbanne] (MATEIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Consortium Lyon Saint-Etienne de Microscopie (CLYM), École normale supérieure - Lyon (ENS Lyon)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet [Saint-Étienne] (UJM), Matériaux, ingénierie et science [Villeurbanne] ( MATEIS ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Consortium Lyon Saint-Etienne de Microscopie ( CLYM ), École normale supérieure - Lyon ( ENS Lyon ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Université Jean Monnet [Saint-Étienne] ( UJM ), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure de Lyon (ENS de Lyon)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)

Subjects
electron tomography, 02 engineering and technology, Imaging techniques, X ray analysis, 01 natural sciences, [SPI.MAT]Engineering Sciences [physics]/Materials, equipment design, Scanning transmission electron microscopy, image quality, Instrumentation, Environmental scanning electron microscope, 010302 applied physics, Resolution (electron density), three dimensional imaging, Low-atomic number materials, article, STEM, 021001 nanoscience & nanotechnology, image reconstruction, ESEM, Atomic and Molecular Physics, and Optics, structure analysis, Electronic, Optical and Magnetic Materials, Characterization (materials science), scanning transmission electron microscopy, 0210 nano-technology, Scanning electron microscopy, Atoms, Materials science, Electric impedance tomography, Three-dimensional characterization, Characterization, [ SPI.MAT ] Engineering Sciences [physics]/Materials, environmental scanning electron microscopy, Electrons, Conductive materials, Optics, process optimization, 0103 physical sciences, atomic particle, Energy filtered transmission electron microscopy, controlled study, image enhancement, High-resolution transmission electron microscopy, intermethod comparison, business.industry, Three dimensional, Scanning confocal electron microscopy, thickness, process development, Non-conductive samples, Electron tomography, business, Large tomogram, Transmission electron microscopy, instrument validation
Abstract

cited By 13; International audience; This paper presents the development and the application of a new electron tomography technique based on STEM (Scanning Transmission Electron Microscopy) configuration in ESEM (Environmental Scanning Electron Microscopy). This combination provides a new approach for the characterization of the 3D structure of materials, as it optimizes a compromise between the resolution level of a few tens of nm and the large tomogram size due to the high thickness of transparency. The method is well adapted for non-conductive samples, and exhibits good contrast even for materials with low atomic number. The paper describes the development of a dedicated stage for this new tomography technique. Taking advantage of the size of the ESEM chamber, the range of tilt angles is not limited by the space around the sample. The performance of this device is illustrated through the three-dimensional characterization of samples issued from materials science and chosen to illustrate the results in resolution, contrast and thickness. © 2011 Elsevier B.V.

Published
2011

2. Automatic Cyclic Alternating Pattern (CAP) analysis: Local and multi-trace approaches

Author

Fantozzi, M. P. T., Faraguna, U., Ugon, A., Ciuti, G., Pinna, A., University of Pisa - Università di Pisa, Systèmes Electroniques (SYEL), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), IRCCS Fondazione Stella Maris [Pisa], ESIEE Paris, and Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)

Subjects
Signal filtering, Physiology, Machine Learning, Visual inspection, Medical Conditions, Medicine and Health Sciences, Clinical Neurophysiology, Brain Mapping, Applied Mathematics, Simulation and Modeling, Electroencephalography, Sleep disorders, Electrophysiology, Bioassays and Physiological Analysis, Brain Electrophysiology, Neurology, Physical Sciences, Engineering and Technology, Medicine, Sleep Stages, Algorithms, Research Article, Sleep Wake Disorders, Computer and Information Sciences, Insomnia, Imaging Techniques, Polysomnography, Science, Neurophysiology, Neuroimaging, Research and Analysis Methods, Case-Control Studies, Humans, Sleep, Machine Learning Algorithms, Artificial Intelligence, [INFO]Computer Science [cs], Support vector machines, Electrophysiological Techniques, Biology and Life Sciences, Bandpass filters, Dyssomnias, Signal Processing, Clinical Medicine, Physiological Processes, Mathematics, Neuroscience
Abstract

International audience; The Cyclic Alternating Pattern (CAP) is composed of cycles of two different electroencephalographic features: an activation A-phase followed by a B-phase representing the background activity. CAP is considered a physiological marker of sleep instability. Despite its informative nature, the clinical applications remain limited as CAP analysis is a time-consuming activity. In order to overcome this limit, several automatic detection methods were recently developed. In this paper, two new dimensions were investigated in the attempt to optimize novel, efficient and automatic detection algorithms: 1) many electroencephalographic leads were compared to identify the best local performance, and 2) the global contribution of the concurrent detection across several derivations to CAP identification. The developed algorithms were tested on 41 polysomnographic recordings from normal (n = 8) and pathological (n = 33) subjects. In comparison with the visual CAP analysis as the gold standard, the performance of each algorithm was evaluated. Locally, the detection on the F4-C4 derivation showed the best performance in comparison with all other leads, providing practical suggestions of electrode montage when a lean and minimally invasive approach is preferable. A further improvement in the detection was achieved by a multi-trace method, the Global Analysis-Common Events, to be applied when several recording derivations are available. Moreover, CAP time and CAP rate obtained with these algorithms positively correlated with the ones identified by the scorer. These preliminary findings support efficient automated ways for the evaluation of the sleep instability, generalizable to both normal and pathological subjects affected by different sleep disorders.

Published
2021

3. Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Author

Alexandra Tinnermann, Dimitri Van De Ville, Cornelia Laule, Sean Mackey, Robert L. Barry, Benjamin De Leener, Anna Pichiecchio, Eva Alonso-Ortiz, Giancarlo Germani, Ali Khatibi, Nico Papinutto, Marc J. Ruitenberg, René Labounek, Nawal Kinany, Francesco Grussu, Michela Fratini, Petr Kudlička, Christophe Lenglet, Kouhei Kamiya, Pierre-Gilles Henry, Julien Cohen-Adad, Richard G. Wise, Deborah Pareto, Tomáš Horák, Jürgen Finsterbusch, Alex Rovira, Todd B. Parrish, Y. Suzuki, George Tackley, Junqian Xu, Falk Eippert, Virginie Callot, Daniel Papp, Laura Barlow, Karla R. Epperson, Charley Gros, Nicole Atcheson, Akifumi Hagiwara, Jan Valošek, Yaou Liu, Patrick Freund, Maria Marcella Laganà, James M. Joers, Marco Battiston, Markus Barth, Adam V. Dvorak, Masaaki Hori, Joo Won Kim, Miloš Keřkovský, Paulo Loureiro de Sousa, Sara Llufriu, Mihael Abramovic, Igor Nestrasil, Kenneth A. Weber, Christine S. Law, Paul Kuntke, Elisabeth Solana, Kristin P. O’Grady, Alexandru Foias, Slawomir Kusmia, Claudia A. M. Wheeler-Kingshott, Hagen H. Kitzler, Alex K. Smith, Nyoman D. Kurniawan, Shannon H. Kolind, Marios C. Yiannakas, Seth A. Smith, Zachary A. Smith, Federico Giove, Tobias Leutritz, Matthew D. Budde, Rebecca S. Samson, Christian Büchel, Kevin S. Epperson, Marek Dostál, Giovanni Savini, Issei Fukunaga, Haleh Karbasforoushan, Loan Mattera, Nikolaus Weiskopf, Guillaume Gilbert, Yazhuo Kong, Ferran Prados, Maryam Seif, Anna J.E. Combes, Julien Doyon, P Wyss, Alan C. Seifert, Carina Arneitz, Eloy Martinez-Heras, Maxime Descoteaux, Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - AP-HM] (CEMEREM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Universitat Oberta de Catalunya (UOC), Universitat Oberta de Catalunya. eHealth Center, Institut Català de la Salut, [Cohen-Adad J] NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada. Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada. Mila - Quebec AI Institute, Montreal, QC, Canada. [Alonso-Ortiz E] NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada. [Abramovic M, Arneitz C] Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland. [Atcheson N] Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia. [Barlow L] Department of Radiology, University of British Columbia, Vancouver, BC, Canada. [Grussu F] NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK. Radiomics Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain. Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Pareto D, Rovira À] Secció de Neuroradiologia, Vall d’Hebron Hospital Universitri, Barcelona, Spain, Vall d'Hebron Barcelona Hospital Campus, Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - APHM] (CEMEREM), Hôpital de la Timone [CHU - APHM] (TIMONE)-Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, and Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Statistics and Probability, Data Descriptor, medicine.medical_specialty, Sciences du Vivant [q-bio]/Neurosciences [q-bio.NC], Investigació - Avaluació, Nervous System::Central Nervous System::Spinal Cord [ANATOMY], databases, Computer science, Science, of-the-art, Spinal cord diseases, Spinal Cord Diseases, Imaging techniques, Library and Information Sciences, 030218 nuclear medicine & medical imaging, Education, Databases, 03 medical and health sciences, 0302 clinical medicine, Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT], Investigative Techniques::Epidemiologic Methods::Epidemiologic Research Design::Reproducibility of Results [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT], medicine, Medical physics, diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS], Other subheadings::Other subheadings::/diagnostic imaging [Other subheadings], Protocol (science), Reproducibility, Extramural, Otros calificadores::Otros calificadores::/diagnóstico por imagen [Otros calificadores], técnicas de investigación::métodos epidemiológicos::diseño de la investigación epidemiológica::reproducibilidad de los resultados [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS], white, Spinal cord, spinal cord diseases, Toolbox, imaging techniques, matter, Computer Science Applications, magnetization-transfer, medicine.anatomical_structure, Imatgeria per ressonància magnètica, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], sistema nervioso::sistema nervioso central::médula espinal [ANATOMÍA], Statistics, Probability and Uncertainty, Medul·la espinal - Malalties - Imatgeria, 030217 neurology & neurosurgery, Information Systems
Abstract

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord., Measurement(s)spinal cordTechnology Type(s)magnetic resonance imagingFactor Type(s)manufacturer • siteSample Characteristic - OrganismHomo sapiensSample Characteristic - LocationCanada • Switzerland • Australia • United States of America • United Kingdom • Germany • French Republic • Czech Republic • Italy • Japan • Kingdom of Spain • China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14052269

Published
2021

4. A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops

Author

Diego Mendez, Eliel Petro, Juan P. Rojas, Maria Camila Rebolledo, Julian Colorado, Andres Jaramillo-Botero, Edgar S. Correa, Francisco Calderon, Iván F. Mondragón, Pontificia universidad Javeriana, Cali, International Center for Tropical Agriculture [Colombie] (CIAT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Image & Interaction (ICAR), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), California Institute of Technology (CALTECH), and ICETEX FP44842-217-2018

Subjects
Canopy, 010504 meteorology & atmospheric sciences, Image Processing, [SDV]Life Sciences [q-bio], Multispectral image, 0211 other engineering and technologies, Biomass, 02 engineering and technology, 01 natural sciences, Imagerie multispectrale, Machine Learning, Spectrum Analysis Techniques, F01 - Culture des plantes, Biomasse, Image Processing, Computer-Assisted, Segmentation, Mathematics, 2. Zero hunger, Multidisciplinary, Applied Mathematics, Simulation and Modeling, near-Infrared Spectroscopy, Eukaryota, Agriculture, Plants, agriculture de précision, Experimental Organism Systems, Physical Sciences, Engineering and Technology, Medicine, Biomasse aérienne, Algorithms, Research Article, Optimization, Crops, Agricultural, Imaging Techniques, Infrared Rays, Traitement d'images, Science, Spectroscopie infrarouge, Crops, Infrared Spectroscopy, Oryza sativa, Image processing, Colombia, Research and Analysis Methods, Phenotypage, Spatio-Temporal Analysis, Plant and Algal Models, Grasses, Cluster analysis, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, business.industry, Organisms, Biology and Life Sciences, Oryza, Pattern recognition, Image segmentation, 15. Life on land, Mixture model, Signal Processing, Remote Sensing Technology, Animal Studies, Geographic Information Systems, Rice, Artificial intelligence, U30 - Méthodes de recherche, business, Crop Science, Cereal Crops
Abstract

International audience; Traditional methods to measure spatio-temporal variations in biomass rely on a labor-intensive destructive sampling of the crop. In this paper, we present a high-throughput phenotyping approach for the estimation of Above-Ground Biomass Dynamics (AGBD) using an unmanned aerial system. Multispectral imagery was acquired and processed by using the proposed segmentation method called GFKuts, that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo based K-means, and a guided image filtering. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. Machine learning algorithms were trained to estimate the AGBD according to the growth stages of the crop and the physiological response of two rice genotypes under lowland and upland production systems. Results report AGBD estimation correlations with an average of r = 0.95 and R 2 = 0.91 according to the experimental data. We compared our segmentation method against a traditional technique based on clustering. A comprehensive improvement of 13% in the biomass correlation was obtained thanks to the segmentation method proposed herein.

Published
2020

5. Model-based estimation of left ventricular pressure and myocardial work in aortic stenosis

Author

Owashi, Kimi P., Hubert, Arnaud, Galli, Elena, Donal, Erwan, Hernández, Alfredo I., Le Rolle, Virginie, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), This work was supported by the French National Research Agency (ANR) (ANR-16-CE19-0008-01) (project MAESTRo) and the French Brittany council (ADvICE project)., ANR-16-CE19-0008,MAESTRo,Approche à base de modèles pour l'analyse du strain obtenu en échocardiographie 3D(2016), Bodescot, Myriam, Approche à base de modèles pour l'analyse du strain obtenu en échocardiographie 3D - - MAESTRo2016 - ANR-16-CE19-0008 - AAPG2016 - VALID, and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Male, Patient-Specific Modeling, Cardiac Ventricles, Imaging Techniques, Science, [SCCO.COMP]Cognitive science/Computer science, Blood Pressure, Surgical and Invasive Medical Procedures, Pathology and Laboratory Medicine, Research and Analysis Methods, Vascular Medicine, Ventricular Function, Left, Diagnostic Radiology, Catheterization, Signs and Symptoms, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Diagnostic Medicine, [SCCO.COMP] Cognitive science/Computer science, Ultrasound Imaging, Medicine and Health Sciences, Ventricular Pressure, Humans, Computer Simulation, Prospective Studies, Aorta, ComputingMilieux_MISCELLANEOUS, Aged, Stenosis, Aged, 80 and over, Radiology and Imaging, Models, Cardiovascular, Biology and Life Sciences, Heart, Stroke Volume, Aortic Valve Stenosis, Myocardial Contraction, Systolic Pressure, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Echocardiography, Aortic Valve, Cardiovascular Anatomy, Medicine, Blood Vessels, Female, Anatomy, Monte Carlo Method, Research Article
Abstract

This paper proposes a model-based estimation of left ventricular (LV) pressure for the evaluation of constructive and wasted myocardial work of patients with aortic stenosis (AS). A model of the cardiovascular system is proposed, including descriptions of i) cardiac electrical activity, ii) elastance-based cardiac cavities, iii) systemic and pulmonary circulations and iv) heart valves. After a sensitivity analysis of model parameters, an identification strategy was implemented using a Monte-Carlo cross-validation approach. Parameter identification procedure consists in two steps for the estimation of LV pressures: step 1) from invasive, intraventricular measurements and step 2) from non-invasive data. The proposed approach was validated on data obtained from 12 patients with AS. The total relative errors between estimated and measured pressures were on average 11.9% and 12.27% and mean R2 were equal to 0.96 and 0.91, respectively for steps 1 and 2 of parameter identification strategy. Using LV pressures obtained from non-invasive measurements (step 2) and patient-specific simulations, Global Constructive (GCW), Wasted (GWW) myocardial Work and Global Work Efficiency (GWE) parameters were calculated. Correlations between measures and model-based estimations were 0.88, 0.80, 0.91 respectively for GCW, GWW and GWE. The main contributions concern the proposal of the parameter identification procedure, applied on an integrated cardiovascular model, able to reproduce LV pressure specifically to each AS patient, by non-invasive procedures, as well as a new method for the non-invasive estimation of constructive, wasted myocardial work and work efficiency in AS.

Published
2020

6. Estimation of intravoxel incoherent motion parameters using low b-values

Author

Lihui Wang, Zi-Xiang Kuai, Rongpin Wang, Chen Ye, Daoyun Xu, Wuchao Li, Yongbin Qin, Yuemin Zhu, CFD Lab [Montréal], Department of Mechanical Engineering [Montréal], McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Statistical Noise, Diagnostic Radiology, 030218 nuclear medicine & medical imaging, Mathematical and Statistical Techniques, 0302 clinical medicine, Image Processing, Computer-Assisted, Medicine and Health Sciences, Prospective Studies, Intravoxel incoherent motion, Mathematics, Multidisciplinary, Radiology and Imaging, Simulation and Modeling, Statistics, Magnetic Resonance Imaging, Gaussian Noise, In Vivo Imaging, Data Acquisition, Physical Sciences, symbols, Medicine, Engineering and Technology, Biological system, Algorithms, Research Article, Shrinkage estimator, Computer and Information Sciences, Imaging Techniques, Science, Bayesian Method, Bayesian probability, Image processing, Research and Analysis Methods, Noise (electronics), Motion, 03 medical and health sciences, symbols.namesake, Diagnostic Medicine, Approximation error, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Signal to Noise Ratio, Models, Theoretical, Signal-to-noise ratio (imaging), Gaussian noise, Signal Processing, 030217 neurology & neurosurgery
Abstract

International audience; Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. However, IVIM imaging at low b-values is a persistent problem. This paper aims to investigate in a systematic and detailed manner how the number of low b-values influences the estimation of IVIM parameters. To this end, diffusion-weighted (DW) data with different low b-values were simulated to get insight into the distributions of subsequent IVIM parameters. Then, in vivo DW data with different numbers of low b-values and different number of excitations (NEX) were acquired. Finally, least-squares (LSQ) and Bayesian shrinkage prior (BSP) fitting methods were implemented to estimate IVIM parameters. The influence of the number of low b-values on IVIM parameters was analyzed in terms of relative error (RE) and structural similarity (SSIM). The results showed that the influence of the number of low b-values on IVIM parameters is variable. LSQ is more dependent on the number of low b-values than BSP, but the latter is more sensitive to noise.

Published
2019

7. Dynamic inking of large-scale stamps for multiplexed microcontact printing and fabrication of cell microarrays

Author

Foncy, Julie, Estève, Aurore, Degache, Amélie, Colin, Camille, Dollat, Xavier, Cau, Jean-Christophe, Vieu, Christophe, Trévisiol, Emmanuelle, Malaquin, Laurent, Service Instrumentation Conception Caractérisation (LAAS-I2C), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Équipe Ingénierie pour les sciences du vivant (LAAS-ELIA), Innopsys [Carbonne], Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
[SDV.BIO]Life Sciences [q-bio]/Biotechnology, Imaging Techniques, Microarrays, Microfluidics, Materials Science, Equipment, lcsh:Medicine, Biosensing Techniques, Fluid Mechanics, Research and Analysis Methods, Continuum Mechanics, Fluorescence Imaging, Cell Adhesion, [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, lcsh:Science, Cell Shape, Materials by Attribute, Flow Rate, Extracellular Matrix Proteins, Physics, lcsh:R, Classical Mechanics, Biology and Life Sciences, Fluid Dynamics, Laboratory Glassware, Cell Biology, Microfluidic Analytical Techniques, Laboratory Equipment, Bioassays and Physiological Analysis, Manufacturing Processes, Tissue Array Analysis, Physical Sciences, Magnets, Printing, Engineering and Technology, lcsh:Q, Fluidics, Research Article
Abstract

International audience; Microcontact printing has become a versatile soft lithography technique used to produce molecular micro-and nano-patterns consisting of a large range of different biomolecules. Despite intensive research over the last decade and numerous applications in the fields of biosensors, microarrays and biomedical applications, the large-scale implementation of microcontact printing is still an issue. It is hindered by the stamp-inking step that is critical to ensure a reproducible and uniform transfer of inked molecules over large areas. This is particularly important when addressing application such as cell microarray manufacturing, which are currently used for a wide range of analytical and pharmaceutical applications. In this paper, we present a large-scale and multiplexed microcontact printing process of extra-cellular matrix proteins for the fabrication of cell microarrays. We have developed a micro-fluidic inking approach combined with a magnetic clamping technology that can be adapted to most standard substrates used in biology. We have demonstrated a significant improvement of homogeneity of printed protein patterns on surfaces larger than 1 cm 2 through the control of both the flow rate and the wetting mechanism of the stamp surface during micro-fluidic inking. Thanks to the reproducibility and integration capabilities provided by microflui-dics, we have achieved the printing of three different adhesion proteins in one-step transfer. Selective cell adhesion and cell shape adaptation on the produced patterns were observed, showing the suitability of this approach for producing on-demand large-scale cell microarrays.

Published
2018

8. Gaze distribution analysis and saliency prediction across age groups

Author

Onkar Krishna, Pia Rämä, Kiyoharu Aizawa, Andrea Helo, Laboratoire Psychologie de la Perception (LPP - UMR 8242), Université Paris Descartes - Paris 5 (UPD5)-Centre National de la Recherche Scientifique (CNRS), and Rämä, Pia

Subjects
FOS: Computer and information sciences, Male, Aging, Visual perception, Eye Movements, genetic structures, Computer science, Vision, Physiology, Visual System, Computer Vision and Pattern Recognition (cs.CV), Entropy, Sensory Physiology, Computer Science - Computer Vision and Pattern Recognition, Social Sciences, lcsh:Medicine, 0302 clinical medicine, Elderly, Medicine and Health Sciences, Psychology, Computer vision, Attention, lcsh:Science, Aged, 80 and over, Multidisciplinary, Physics, 05 social sciences, Middle Aged, Sensory Systems, Human visual system model, Physical Sciences, [SCCO.PSYC] Cognitive science/Psychology, [SCCO.PSYC]Cognitive science/Psychology, Visual Perception, Thermodynamics, Sensory Perception, Research Article, Adult, Imaging Techniques, Fixation, Ocular, Research and Analysis Methods, 050105 experimental psychology, 03 medical and health sciences, Age groups, Salience (neuroscience), Visual attention, Humans, 0501 psychology and cognitive sciences, Saliency map, Aged, Behavior, business.industry, lcsh:R, Cognitive Psychology, Eye movement, Biology and Life Sciences, Pattern recognition, Gaze, Age Groups, People and Places, Cognitive Science, Population Groupings, lcsh:Q, Artificial intelligence, business, 030217 neurology & neurosurgery, Neuroscience
Abstract

International audience; Knowledge of the human visual system helps to develop better computational models of visual attention. State-of-the-art models have been developed to mimic the visual attention system of young adults that, however, largely ignore the variations that occur with age. In this paper, we investigated how visual scene processing changes with age and we propose an age-adapted framework that helps to develop a computational model that can predict saliency across different age groups. Our analysis uncovers how the explorativeness of an observer varies with age, how well saliency maps of an age group agree with fixation points of observers from the same or different age groups, and how age influences the center bias tendency. We analyzed the eye movement behavior of 82 observers belonging to four age groups while they explored visual scenes. Explorative-ness was quantified in terms of the entropy of a saliency map, and area under the curve (AUC) metrics was used to quantify the agreement analysis and the center bias tendency. Analysis results were used to develop age adapted saliency models. Our results suggest that the proposed age-adapted saliency model outperforms existing saliency models in predicting the regions of interest across age groups.

Published
2018

9. GPU accelerated simulations of magnetic resonance imaging of vascular structures

Author

Johanne Bezy-Wendling, Krzysztof Jurczuk, Marek Kretowski, Dariusz Murawski, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Parallel-computing environment, Computer science, Memory hierarchy, 0206 medical engineering, Vascular structures, 02 engineering and technology, Imaging techniques, 030204 cardiovascular system & hematology, Tracking (particle physics), Computational power, Resonance, Computational science, 03 medical and health sciences, CUDA, Computer graphics, 0302 clinical medicine, Magnetic resonance imaging, Computer graphics equipment, medicine, ComputingMethodologies_COMPUTERGRAPHICS, Modality (human–computer interaction), medicine.diagnostic_test, Parallel processing systems, Magnetism, Spatial coordinates, Computer simulation, Imaging modality, Program processors, 020601 biomedical engineering, Power (physics), Computer Science::Graphics, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Perfusion, Graphics Processing Unit, Spatial and temporal resolutions
Abstract

International audience; Computer simulations of magnetic resonance imaging (MRI) are important tools in improving this imaging modality and developing new imaging techniques. However, MRI models often have to be simplified to enable simulations to be carried out in a reasonable time. The computational complexity associated with the tracking of magnetic fields’ perturbations with high spatial and temporal resolutions is very high and, thus, it calls for using parallel computing environments. In this paper, we present a GPU-based parallel approach to simulate MRI of vascular structures. The magnetization calculation in different spatial coordinates is spread over GPU cores. We apply CUDA framework and take advantage of GPU memory hierarchy to efficiently exploit GPU computational power. Experimental results with different GPUs and various images show that the proposed algorithm substantially speedups the simulation. The proposed GPU-based approach may be easily adopted in modeling of other flow related phenomena like perfusion or diffusion. © Springer International Publishing Switzerland 2016.

Published
2015

10. New Concepts in Molecular Imaging: Non-Invasive MRI Spotting of Proteolysis Using an Overhauser Effect Switch

Author

Guillaume Madelin, Philippe Mellet, Etienne Harté, Eric Thiaudière, Jean-Michel Franconi, Philippe Massot, Sylvain R. A. Marque, Centre de résonance magnétique des systèmes biologiques (CRMSB), Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB), Laboratoire Chimie Provence (LCP), Centre National de la Recherche Scientifique (CNRS)-Université de Provence - Aix-Marseille 1-Institut de Chimie du CNRS (INC), Centre de recherches Paul Pascal (CRPP), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), and Université de Provence - Aix-Marseille 1-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Diagnostic Imaging, Proteases, Proteolysis, medicine.medical_treatment, [PHYS.PHYS.PHYS-BIO-PH]Physics [physics]/Physics [physics]/Biological Physics [physics.bio-ph], lcsh:Medicine, Biochemistry/Biocatalysis, Free radicals, Imaging techniques, 010402 general chemistry, 01 natural sciences, Biochemistry, Models, Biological, Magnetic resonance imaging, Electron spin resonance spectroscopy, medicine, Medical imaging, Animals, Cysteine, Biophysics/Biocatalysis, lcsh:Science, Biochemistry/Experimental Biophysical Methods, Multidisciplinary, Protease, Cysteine proteases, medicine.diagnostic_test, 010405 organic chemistry, Hydrolysis, lcsh:R, Radiology and Medical Imaging/Magnetic Resonance Imaging, Proteins, Serum Albumin, Bovine, Mathematical Concepts, In vitro, 0104 chemical sciences, In vivo imaging, Biophysics, lcsh:Q, Cattle, Nitrogen Oxides, Molecular imaging, Preclinical imaging, Research Article, Peptide Hydrolases
Abstract

9 pages; International audience; Background: Proteolysis, involved in many processes in living organisms, is tightly regulated in space and time under physiological conditions. However deregulation can occur with local persistent proteolytic activities, e.g. in inflammation, cystic fibrosis, tumors, or pancreatitis. Furthermore, little is known about the role of many proteases, hence there is a need of new imaging methods to visualize specifically normal or disease-related proteolysis in intact bodies. Methodology/Principal Findings: In this paper, a new concept for non invasive proteolysis imaging is proposed. Overhauser-enhanced Magnetic Resonance Imaging (OMRI) at 0.2 Tesla was used to monitor the enzymatic hydrolysis of a nitroxide-labeled protein. In vitro, image intensity switched from 1 to 25 upon proteolysis due to the associated decrease in the motional correlation time of the substrate. The OMRI experimental device used in this study is consistent with protease imaging in mice at 0.2 T without significant heating. Simulations show that this enzymatic-driven OMRI signal switch can be obtained at lower frequencies suitable for larger animals or humans. Conclusions/Significance: The method is highly sensitive and makes possible proteolysis imaging in three dimensions with a good spatial resolution. Any protease could be targeted specifically through the use of taylor-made cleavable macromolecules. At short term OMRI of proteolysis may be applied to basic research as well as to evaluate therapeutic treatments in small animal models of experimental diseases.

Published
2009

11. A new Log-Polar Mapping for Space Variant Imaging : Application to Face Detection and Tracking

Author

Jurie, Frédéric, image, Laboratoire des sciences et matériaux pour l'électronique et d'automatique (LASMEA), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS), and Team, THOTH

Subjects
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Image coding, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Image sensors, Space variant images, Imaging techniques, Face detection, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Computer Science::Computer Vision and Pattern Recognition, Pattern recognition, Functions, Computer vision, Log polar sensor, Image representation
Abstract

International audience; Space-variant images (images whose resolution changes across the image) supply a powerful image representation for active vision systems. In this article a new log-polar mapping is presented. The main originality of this mapping is its great flexibility. Unlike other approaches the range of the logarithmic function used for the mapping can be fully specified (width and position). In this paper we also propose several efficient algorithms performing basic operations on these images. The originality of the proposed encoding is that log-polar pixels are a fractional part of rectangular pixels. Finally, we present some experimental results describing the use of this mapping in a face detection and tracking application.

Published
1999