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76 results on '"Christophe Tilmant"'

1. Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging.

Author

Jessica Lebenberg, Alain Lalande, Patrick Clarysse, Irene Buvat, Christopher Casta, Alexandre Cochet, Constantin Constantinidès, Jean Cousty, Alain de Cesare, Stephanie Jehan-Besson, Muriel Lefort, Laurent Najman, Elodie Roullot, Laurent Sarry, Christophe Tilmant, Frederique Frouin, and Mireille Garreau

Subjects
Medicine, Science
Abstract

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert.

Published
2015
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9. Segmentation

Author

David Tschumperlé, Christophe Tilmant, and Vincent Barra

Published
2023

10. Introduction

Author

David Tschumperlé, Christophe Tilmant, and Vincent Barra

Published
2023

11. Filtering

Author

David Tschumperlé, Christophe Tilmant, and Vincent Barra

Published
2023

13. 3D Visualisation

Author

David Tschumperlé, Christophe Tilmant, and Vincent Barra

Published
2023

16. Feature Extraction

Author

David Tschumperlé, Christophe Tilmant, and Vincent Barra

Published
2023

18. Motion Estimation

Author

David Tschumperlé, Christophe Tilmant, and Vincent Barra

Published
2023

20. A mutual reference shape based on information theory.

Author

Stéphanie Jehan-Besson, Christophe Tilmant, Alain De Cesare, Alain Lalande, Alexandre Cochet, Jean Cousty, Jessica Lebenberg, Muriel Lefort, Patrick Clarysse, Régis Clouard, Laurent Najman, Laurent Sarry, Frédérique Frouin, and Mireille Garreau

Published
2014
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30. Comparison of different segmentation approaches without using gold standard. Application to the estimation of the left ventricle ejection fraction from cardiac cine MRI sequences.

Author

Jessica Lebenberg, Irène Buvat, Mireille Garreau, Christopher Casta, Constantin Constantinides, Jean Cousty, Alexandre Cochet, Stéphanie Jehan-Besson, Christophe Tilmant, Muriel Lefort, Elodie Roullot, Laurent Najman, Laurent Sarry, Patrick Clarysse, Alain De Cesare, Alain Lalande, and Frédérique Frouin

Published
2011
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38. Nonsupervised Ranking of Different Segmentation Approaches: Application to the Estimation of the Left Ventricular Ejection Fraction From Cardiac Cine MRI Sequences.

Author

Jessica Lebenberg, Irène Buvat, Alain Lalande, Patrick Clarysse, Christopher Casta, Alexandre Cochet, Constantin Constantinides, Jean Cousty, Alain De Cesare, Stéphanie Jehan-Besson, Muriel Lefort, Laurent Najman, Elodie Roullot, Laurent Sarry, Christophe Tilmant, Mireille Garreau, and Frédérique Frouin

Published
2012
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41. Automatic Calibration of Hybrid Dynamic Vision System for High Resolution Object Tracking

Author

Quoc Cuong Pham, Patrick Sayd, Julie Badri, Jean-Marc Lavest, and Christophe Tilmant

Subjects
Pixel, business.industry, Orientation (computer vision), Machine vision, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Tracking system, Field of view, Computer Science::Computer Vision and Pattern Recognition, Video tracking, Computer vision, Artificial intelligence, business, Focus (optics), Projection (set theory), ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Visual object recognition and tracking require a good resolution of the object to accurately model its appearance. In addition, tracking systems must be able to robustly recover moving target trajectory, and possibly cope with fast motion and large displacements. Wide angle static cameras capture a global view of the scene but they suffer from a lack of resolution in the case of a large distance between the objects and the sensor. On the contrary, dynamic sensors such as Pan-Tilt-Zoom (PTZ) cameras are controlled to focus on a 3D point in the scene and give access to high resolution images by adapting their zoom level. However, when a PTZ camera focuses on a target, its very limited field of view makes the tracking difficult. To overcome these limitations, hybrid sensor systems composed of a wide angle static camera and a dynamic camera can be used. Coupling these two types of sensors enables the exploitation of their complementary desired properties while limiting their respective drawbacks. Calibration is required to enable information exchange between the two sensors to produce collaborative algorithms. The calibration of our system is difficult because of changes of both intrinsic (focal length, central point, distortion) and extrinsic (position, orientation) parameters of the dynamic sensor during system exploitation. Two approaches for dynamic stereo sensor calibration are possible: • Strong calibration involves a complete modeling of the system. Intrinsic parameters of each camera and extrinsic parameters are estimated. This approach enables the projection of 3D points, expressed in the world frame, in 2D points expressed in each image frame. • Weak calibration does not target to estimate intrinsic or extrinsic parameters. The objective is only to estimate the direct relation between pixels of the different sensors. From a pixel in the first camera, which is the projection of a given 3D point, the calibration gives the projection of the same 3D point to the second camera. In this approach, the recovery of 3D point coordinates is not more difficult.

Published
2021

42. Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery

Author

Karim Botros, Lilian Calvet, Adrien Bartoli, Christophe Tilmant, Emmanuel Buc, Yamid Espinel, and Université Clermont Auvergne (UCA)

Subjects
Liver surgery, Monocular, Computer science, business.industry, 0206 medical engineering, Visibility (geometry), 02 engineering and technology, Patient data, 020601 biomedical engineering, Clinical Practice, [SPI]Engineering Sciences [physics], Margin (machine learning), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Augmented reality, Artificial intelligence, Single image, business, ComputingMilieux_MISCELLANEOUS
Abstract

Deformable registration is required to achieve laparoscopic augmented reality but still is an open problem. Some of the existing methods reconstruct a preoperative model and register it using anatomical landmarks from a single image. This is not accurate due to depth ambiguities. Other methods require of non-standard devices unadapted to the clinical practice. A reasonable way to improve accuracy is to combine multiple images from a monocular laparoscope. We propose three novel registration methods exploiting information from multiple images. The first two are based on rigidly-related images (MV-B and MV-C) and the third one on non-rigidly-related images (MV-D). We evaluated registration accuracy quantitatively on synthetic and phantom data, and qualitatively on patient data, comparing our results with state of the art methods. Our methods outperforms, reducing the partial visibility and depth ambiguity issues of single-view approaches. We characterise the improvement margin, which may be slight or significant, depending on the scenario.

Published
2021

43. Digital Image Processing with C++ : Implementing Reference Algorithms with the CImg Library

Author

David Tschumperle, Christophe Tilmant, Vincent Barra, David Tschumperle, Christophe Tilmant, and Vincent Barra

Subjects
Libraries (Computer program subroutines), Image processing--Digital techniques--Computer programs, C++ (Computer program language)
Abstract

Digital Image Processing with C++: Implementing Reference Algorithms with the CImg Library presents the theory of digital image processing and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language using the free and easy-to-use CImg library.Chapters cover the field of digital image processing in a broad way and propose practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization.Students or developers wishing to discover or specialize in this discipline and teachers and researchers hoping to quickly prototype new algorithms or develop courses will all find in this book material to discover image processing or deepen their knowledge in this field.

Published
2023

44. Mutual cineMR/RT3DUS cardiac segmentation

Author

Christophe Tilmant, Frédéric Chausse, and Clément Beitone

Subjects
Computer science, business.industry, Heart Ventricles, Ultrasound, Echocardiography, Three-Dimensional, Scale-space segmentation, Magnetic Resonance Imaging, Cine, Image segmentation, Level set, Match moving, cardiovascular system, Image Processing, Computer-Assisted, Humans, Segmentation, Computer vision, Affine transformation, Artificial intelligence, business, Volume (compression)
Abstract

We present a new method to segment a cardiac RT3D ultrasound volume by integrating the registered segmentation of a cardiac cine-MR series in short axis of the same patient. The motivation behind our method is to improve the ultrasound segmentation process by integrating a reference shape built using the cine-MR segmentation on the same patient. As a side effect we obtain a close registration of the cine MR short axis slices with respect to the ultrasound volume. We use the level set framework with a functional including a region-based and a shape-based term. The reference shape is iteratively registered onto the contour during the ultrasound segmentation process and using an affine transform. The proposed method is demonstrated on the MICCAI11 Motion Tracking Challenge database.

Published
2016

45. Applying a Gad Filter to Calculate Heat Sources from Noisy Temperature Fields

Author

Christophe Tilmant, Clément Beitone, Michel Grédiac, D. Delpueyo, Frédéric Chausse, and Xavier Balandraud

Subjects
Physics, symbols.namesake, Robustness (computer science), Anisotropic diffusion, Acoustics, Gaussian, Thermography, Electronic engineering, symbols, Image processing, Filter (signal processing), Composite image filter
Abstract

This study deals with a post-processing technique to reconstruct heat source fields from temperature fields measured by infrared thermography. A Gradient Anisotropic Diffusion (GAD) image filter is used to process the data. The technique is first described. Synthetic temperature fields corrupted by added noise are then considered to assess the robustness of the procedure and the filter is optimized in order to reconstruct at best the heat source fields. Results are compared with those obtained with an averaging filter and a Gaussian derivative filter. The second part of the study presents an application to experimental temperature fields. Obtained results illustrate the relevancy of the GAD filter to reliably extract heat sources in thermomechanics of materials.

Published
2016

46. Détection et localisation d’objets stationnaires par une paire de caméras PTZ

Author

Patrick Sayd, Christophe Tilmant, Jean-Marc Lavest, Quoc Cuong Pham, and Constant Guillot

Subjects
Electrical and Electronic Engineering
Abstract

Dans ce papier, nous proposons une approche originale pour detecter et localiser des objets stationnaires sur une scene etendue en exploitant une paire de cameras PTZ. Nous proposons deux contributions principales. Tout d'abord, nous presentons une methode de detection et de segmentation d'objets stationnaires. Celle-ci est basee sur la reidentification de descripteurs de l'avant-plan et une segmentation de ces blobs en objets a l'aide de champs de Markov. La seconde contribution concerne la mise en correspondance entre les deux PTZ des silhouettes d'objets detectees dans chaque image.

Published
2012

47. Multimodal quantification and validation of 3D regional myocardial function

Author

Jérôme Pousin, L. Cassagnes, V. Tuyisenge, Pierre Croisille, Frédéric Chausse, C. Merlin, Clément Beitone, Patrick Clarysse, Guillaume Clerfond, Antoine Vacavant, Christophe Tilmant, Kevin Bianchi, P. Bouges, R. Stoica, Laurent Sarry, Institut Pascal (IP), SIGMA Clermont (SIGMA Clermont)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-SIGMA Clermont (SIGMA Clermont)-Centre National de la Recherche Scientifique (CNRS), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-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)-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), Université de Lyon-Institut National des Sciences Appliquées (INSA)-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), Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne), Centre Jean Perrin [Clermont-Ferrand] (UNICANCER/CJP), UNICANCER, Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Institut Pascal ( IP ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Sigma CLERMONT ( Sigma CLERMONT ) -Centre National de la Recherche Scientifique ( CNRS ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Kéosys, 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-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 ) -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 ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -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 ), CHU Clermont-Ferrand, Centre Hospitalier Universitaire de Saint-Etienne ( CHU de Saint-Etienne ), Centre Jean Perrin, CRLCC Jean Perrin, Institut Camille Jordan [Villeurbanne] ( ICJ ), 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 ) -Centre National de la Recherche Scientifique ( CNRS ), ANR-11-TECS-0002,3DSTRAIN,Quantification multimodale et validation de la fonction myocardique régionale 3D ( 2011 ), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-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), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Modélisation mathématique, calcul scientifique (MMCS), Institut Camille Jordan (ICJ), 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)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), ANR-11-TECS-0002,3DSTRAIN,Quantification multimodale et validation de la fonction myocardique régionale 3D(2011), 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)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet [Saint-Étienne] (UJM)-Centre National de la Recherche Scientifique (CNRS)-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)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Modalities, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, business.industry, media_common.quotation_subject, Biomedical Engineering, Biophysics, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, Clinical routine, Machine learning, computer.software_genre, Myocardial function, [SPI.AUTO]Engineering Sciences [physics]/Automatic, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Medicine, Artificial intelligence, business, computer, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Normality, Cardiac imaging, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, ComputingMilieux_MISCELLANEOUS, Biomedical engineering, media_common
Abstract

International audience; The aim of this project is to design a generic formalism for parietal and regional tracking of the left ventricle (LV) and to adapt it to 3D+t3D+t cardiac imaging modalities used in clinical routine (echocardiography, gated-SPECT, cine-MRI). The estimated displacement field must be reliable enough and insensitive to various artifacts to assess regional myocardial function in 3D from the accurate and precise computation of strain. The strain has recently proved to be of great interest for diagnosis and prognostic in cardiology, but its interpretation remains difficult because of the relative nature of the indices. The clinical objective of the 3DStrain project is to bring answers about the knowledge of normality.

Published
2015

49. How big is this neoplasia? live colonoscopic size measurement using the Infocus-Breakpoint

Author

Adrien Bartoli, Francois Chadebecq, and Christophe Tilmant

Subjects
Colonoscopy, Health Informatics, Size measurement, Colonoscopes, Sensitivity and Specificity, Imaging phantom, Pattern Recognition, Automated, Imaging, Three-Dimensional, Artificial Intelligence, Image Interpretation, Computer-Assisted, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Computer vision, Depth of field, Absolute scale, Monocular, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Phantoms, Imaging, Breakpoint, Reproducibility of Results, Image Enhancement, Computer Graphics and Computer-Aided Design, Tumor Burden, Computer Vision and Pattern Recognition, Artificial intelligence, business, Colorectal Neoplasms, Algorithms
Abstract

Colonoscopy is the reference medical examination for early diagnosis and treatment of colonic diseases. This minimally invasive technique allows endoscopists to explore the colon cavity and remove neoplasias – abnormal growths of tissue – which may develop into malignant tumors. The size, shape and appearance of a neoplasia are essential cues for diagnostic. However, the size is difficult to estimate because the absolute scale of the observed tissue is not directly conveyed in the 2D colonoscopic images. An erroneous size estimate may lead to inappropriate treatment. There currently exist no solutions to reproducible neoplasia size measurement adapted to colonoscopy. We propose a colonoscopic size measurement system for neoplasias. By using a simple planar geometry, the key technical problem is reduced to resolving scale. Our core contribution is introducing the Infocus-Breakpoint (IB) that allows us to resolve scale from a regular colonoscopic video. We define the IB as the lower limit of the colonoscope’s depth of field. The IB corresponds to a precise colonoscope to tissue distance, called the reference depth , which we calibrate preoperatively. We detect the IB intraoperatively thanks to two novel modules: deformable Blur-Estimating Tracking (BET) and Blur-Model Fitting (BMF). With our system, the endoscopist may interactively measure the length and area of a neoplasia in a 2D colonoscopic image directly. Our system needs no hardware modification to standard monocular colonoscopes, yet reaching a size measurement accuracy of the order of a millimeter, as shown on several phantom and patient datasets.

Published
2014

50. Improved estimation of the left ventricular ejection fraction using a combination of independent automated segmentation results in cardiovascular magnetic resonance imaging

Author

jessica lebenberg, Alain Lalande, Patrick Clarysse, Irène Buvat, Christopher Casta, Alexandre Cochet, Constantin Constantinides, Jean Cousty, Alain de Cesare, Stéphanie Jehan-Besson, Muriel Lefort, Laurent Najman, Elodie Roullot, Laurent Sarry, Christophe Tilmant, Frédérique Frouin, Mireille Garreau, Lebenberg, Jessica, Laboratoire d'Imagerie Fonctionnelle (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), 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)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service Hospitalier Frédéric Joliot (SHFJ), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, ESME Sudria, Pôle de Recherche en Ingénierie Appliquée à la Médecine (PRIAM), ESME Sudria [Paris]-ESME Sudria [Paris], Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Image Science for Interventional Techniques (ISIT), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Centre National de la Recherche Scientifique (CNRS), Institut Pascal (IP), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-SIGMA Clermont (SIGMA Clermont)-Centre National de la Recherche Scientifique (CNRS), 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), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-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)-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), Université de Lyon-Institut National des Sciences Appliquées (INSA)-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 Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-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), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-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 de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Imagerie Fonctionnelle ( LIF ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -IFR14-IFR49-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), 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 ), Université de Lyon-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 ) -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 ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Service Hospitalier Frédéric Joliot ( SHFJ ), Direction de Recherche Fondamentale (CEA) ( DRF (CEA) ), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay, Pôle de Recherche en Ingénierie Appliquée à la Médecine ( PRIAM ), Laboratoire d'Informatique Gaspard-Monge ( LIGM ), Université Paris-Est Marne-la-Vallée ( UPEM ) -École des Ponts ParisTech ( ENPC ) -ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique ( CNRS ), Image Science for Interventional Techniques ( ISIT ), Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université-Centre National de la Recherche Scientifique ( CNRS ), Institut Pascal ( IP ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Sigma CLERMONT ( Sigma CLERMONT ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Traitement du Signal et de l'Image ( LTSI ), 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
[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/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, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [ SDV.MHEP.CSC ] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
Abstract

—This work aimed at combining different segmenta-tion approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by focusing on the left ventricular ejection fraction (LVEF) estimate resulting from the LV contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations, were studied, and sixteen combinations of the five automated methods were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates of the LVEF than individual automated segmentation methods. In addition, LVEF obtained with STAPLE were within inter-expert variability. Overall, combining different automated segmentation methods improved the reliability of the segmenta-tion result compared to that obtained using an individual method

Published
2014

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