Automatic spinal cord localization, robust to MRI contrasts using global curve optimization

Author:

Gros Charley,De Leener Benjamin,Dupont Sara M.,Martin Allan R.,Fehlings Michael G.,Bakshi Rohit,Tummala Subhash,Auclair Vincent,McLaren Donald G.,Callot Virginie,Cohen-Adad Julien,Sdika Michaël

Funder

Canada Research Chair in Quantitative Magnetic Resonance Imaging

Canadian Institute of Health Research

Canada Foundation for Innovation

Fonds de Recherche du Québec - Santé

Fonds de Recherche du Québec - Nature et Technologies

Natural Sciences and Engineering Research Council of Canada

French National Research Agency

Université de Lyon, "Investissements d'Avenir

National Multiple Sclerosis Society

Centre National de la Recherche Scientifique

Fondation Aix-MArseille Université

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference37 articles.

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3. Accurate quantification methods to evaluate cervical cord atrophy in multiple sclerosis patients;Carbonell-Caballero;Magma,2006

4. Spinal cord atrophy as a primary outcome measure in phase II trials of progressive multiple sclerosis;Cawley;Multiple Sclerosis,2017

5. Automatic magnetic resonance spinal cord segmentation with topology constraints for variable fields of view;Chen;NeuroImage,2013

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