B-spline Based Multi-organ Detection in ...
Type de document :
Compte-rendu et recension critique d'ouvrage
DOI :
Titre :
B-spline Based Multi-organ Detection in Magnetic Resonance Imaging
Auteur(s) :
Jiang, Zhifan [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Witz, Jean-Francois [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Lecomte-Grosbras, M [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Dequidt, Jeremie [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Deformable Robots Simulation Team [DEFROST ]
Duriez, Christian [Auteur]
Deformable Robots Simulation Team [DEFROST ]
Cosson, Michel [Auteur]
Centre Hospitalier Régional Universitaire [CHU Lille] [CHRU Lille]
Cotin, Stéphane [Auteur]
Computational Anatomy and Simulation for Medicine [MIMESIS]
Brieu, M [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Witz, Jean-Francois [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Lecomte-Grosbras, M [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Dequidt, Jeremie [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Deformable Robots Simulation Team [DEFROST ]
Duriez, Christian [Auteur]
Deformable Robots Simulation Team [DEFROST ]
Cosson, Michel [Auteur]
Centre Hospitalier Régional Universitaire [CHU Lille] [CHRU Lille]
Cotin, Stéphane [Auteur]
Computational Anatomy and Simulation for Medicine [MIMESIS]
Brieu, M [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Titre de la revue :
Strain
Pagination :
235 - 247
Éditeur :
Wiley-Blackwell
Date de publication :
2015
ISSN :
0039-2103
Mot(s)-clé(s) en anglais :
B-spline
MR images
pelvic organs detection
virtual image correlation
MR images
pelvic organs detection
virtual image correlation
Discipline(s) HAL :
Informatique [cs]
Informatique [cs]/Imagerie médicale
Physique [physics]/Mécanique [physics]/Biomécanique [physics.med-ph]
Informatique [cs]/Imagerie médicale
Physique [physics]/Mécanique [physics]/Biomécanique [physics.med-ph]
Résumé en anglais : [en]
In the context of the female pelvic medicine, non-invasive Magnetic Resonance Imaging (MRI) is widely used for the diagnosis of pelvic floor disorders. Nowadays in the clinical routine, diagnoses rely largely on human ...
Lire la suite >In the context of the female pelvic medicine, non-invasive Magnetic Resonance Imaging (MRI) is widely used for the diagnosis of pelvic floor disorders. Nowadays in the clinical routine, diagnoses rely largely on human interpretation of medical images, on the experience of physicians, with sometimes subjective interpretations. Hence, image correlation methods would be an alternative way to assist physicians to provide more objective analyses with standard procedures and parametrization for patient-specific cases. Moreover, the main symptoms of pelvic system pathologies are abnormal mobilities. The FEM (Finite Element Model) simulation is a powerful tool for understanding such mobilities. Both the patient-specific simulation and the image analysis require accurate and smooth geometries of the pelvic organs. This paper introduces a new method that can be classified as a model-to-image correlation approach. The method performs fast semi-automatic detection of the bladder, vagina and rectum from MR images for geometries reconstruction and further study of the mobilities. The approach consists of fitting a B-spline model to the organ shapes in real images via a generated virtual image. We provided efficient, adaptive and consistent segmentation on a dataset of 19 patient images (healthy and pathological).Lire moins >
Lire la suite >In the context of the female pelvic medicine, non-invasive Magnetic Resonance Imaging (MRI) is widely used for the diagnosis of pelvic floor disorders. Nowadays in the clinical routine, diagnoses rely largely on human interpretation of medical images, on the experience of physicians, with sometimes subjective interpretations. Hence, image correlation methods would be an alternative way to assist physicians to provide more objective analyses with standard procedures and parametrization for patient-specific cases. Moreover, the main symptoms of pelvic system pathologies are abnormal mobilities. The FEM (Finite Element Model) simulation is a powerful tool for understanding such mobilities. Both the patient-specific simulation and the image analysis require accurate and smooth geometries of the pelvic organs. This paper introduces a new method that can be classified as a model-to-image correlation approach. The method performs fast semi-automatic detection of the bladder, vagina and rectum from MR images for geometries reconstruction and further study of the mobilities. The approach consists of fitting a B-spline model to the organ shapes in real images via a generated virtual image. We provided efficient, adaptive and consistent segmentation on a dataset of 19 patient images (healthy and pathological).Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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