Automatic methods for multiple sclerosis new lesions detection and segmentation

Autor: Olivier Commowick, Benoit Combès, Frederic Cervenansky, Michel Dojat

Publikováno v: Frontiers Research Topics ISBN: 9782832520376

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9b96e7882477d7dd6a0cd524b5bddd17
https://doi.org/10.3389/978-2-83252-037-6

Robustness of spatio-temporal regularization in perfusion MRI deconvolution: An application to acute ischemic stroke

Autor: Frederic Cervenansky, David Rousseau, Marc Robini, Mathilde Giacalone, Emmanuel Grenier, Carole Frindel

Publikováno v: Magnetic Resonance in Medicine. 78:1981-1990

Purpose The robustness of a recently introduced globally convergent deconvolution algorithm with temporal and edge-preserving spatial regularization for the deconvolution of dynamic susceptibility contrast perfusion magnetic resonance imaging is asse

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::63ac8b9bb017133474310dbfc856f1f9
https://doi.org/10.1002/mrm.26573

Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography

Autor: Erik Smistad, Florian Espinosa, Torvald Espeland, Pierre-Marc Jodoin, Erik Andreas Rye Berg, Frederic Cervenansky, Olivier Bernard, Jan D'hooge, Lasse Lovstakken, Andreas Ostvik, João Pedrosa, Thomas Grenier, Sarah Leclerc, Carole Lartizien

Publikováno v: IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2019, 38 (9), pp.2198-2210. ⟨10.1109/TMI.2019.2900516⟩
IEEE Transactions on Medical Imaging, 2019, 38 (9), pp.2198-2210. ⟨10.1109/TMI.2019.2900516⟩

Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has been the subject of intense research. In this paper, we evaluate how far

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec7737d7deba1b24ce6f1c34f273fcaa
https://hal.archives-ouvertes.fr/hal-02054458/file/tmi_2019_Leclerc.pdf

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

Autor: Franca Wagner, Sorina Camarasu-Pop, Hélène Urien, Isabelle Bloch, Xavier Tomas-Fernandez, Jeremy Beaumont, John Muschelli, Chunliang Wang, Baptiste Laurent, Charles R.G. Guttmann, Tristan Glatard, Michael Kain, Mathieu Simon, Michel Dojat, April Khademi, Martin Styner, Pascal Girard, Thomas Tourdias, Michel M. dos Santos, Wellington Pinheiro dos Santos, Sergi Valverde, Richard McKinley, Abel G. Silva-Filho, Jesse Knight, Eloy Roura, Sandra Vukusic, Francisco Javier Vera-Olmos, François Cotton, Xavier Lladó, Elizabeth M. Sweeney, Senan Doyle, Anne Kerbrat, Olivier Commowick, Mariano Cabezas, Florent Leray, Amirreza Mahbod, Norberto Malpica, Gilles Edan, Roxana Ameli, Christian Barillot, Frederic Cervenansky, Florence Forbes, Simon K. Warfield, Audrey Istace, Jean-Christophe Ferré

Publikováno v: Scientific Reports
Scientific Reports, 2018, 8 (1), pp.13650. ⟨10.1038/s41598-018-31911-7⟩
Scientific Reports, 2018. vol. 8, núm. art.13650
Articles publicats (D-ATC)
DUGiDocs – Universitat de Girona
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Scientific Reports, Nature Publishing Group, 2018, 8 (1), pp.13650. ⟨10.1038/s41598-018-31911-7⟩
Commowick, Olivier; Istace, Audrey; Kain, Michaël; Laurent, Baptiste; Leray, Florent; Simon, Mathieu; Pop, Sorina Camarasu; Girard, Pascal; Améli, Roxana; Ferré, Jean-Christophe; Kerbrat, Anne; Tourdias, Thomas; Cervenansky, Frédéric; Glatard, Tristan; Beaumont, Jérémy; Doyle, Senan; Forbes, Florence; Knight, Jesse; Khademi, April; Mahbod, Amirreza; ... (2018). Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure. Scientific Reports, 8(1), p. 13650. Nature Publishing Group 10.1038/s41598-018-31911-7
Scientific Reports, Vol 8, Iss 1, Pp 1-17 (2018)
Scientific Reports, Nature Publishing Group, 2018, 8, pp.13650. ⟨10.1038/s41598-018-31911-7⟩

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evalu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a22615f2bb6870e954083e763f94d4a5
http://www.hal.inserm.fr/inserm-01847873

The first MICCAI challenge on PET tumor segmentation

Autor: Shan Tan, Christian Barillot, Frederic Cervenansky, Vincent Jaouen, Witold Dyrka, Anouar Ouahabi, Tristan Glatard, Hadi Fayad, Sorina Camarasu-Pop, Wei Lu, Baptiste Laurent, Clovis Tauber, Filip Drapejkowski, Pascal Girard, Yao Yao, Laquan Li, Michael Kain, Assen S. Kirov, Dimitris Visvikis, Mathieu Hatt, Jakub Czakon

Publikováno v: Medical Image Analysis
Medical Image Analysis, Elsevier, 2018, 44, pp.177-195. ⟨10.1016/j.media.2017.12.007⟩
Medical Image Analysis, 2018, 44, pp.177-195. ⟨10.1016/j.media.2017.12.007⟩
Med Image Anal

Introduction Automatic functional volume segmentation in PET images is a challenge that has been addressed using a large array of methods. A major limitation for the field has been the lack of a benchmark dataset that would allow direct comparison of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a42c12876e62d29a5c3b0ab18d0e1b8
https://hal.archives-ouvertes.fr/hal-01659162/file/manuscript_final.pdf