Open AccessDeep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis
Author(s) -
Ivan Coronado,
Refaat E. Gabr,
Ponnada A. Narayana
Publication year - 2020
Publication title -
multiple sclerosis journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.729
H-Index - 131
eISSN - 1477-0970
pISSN - 1352-4585
DOI - 10.1177/1352458520921364
Subject(s) - gadolinium , fluid attenuated inversion recovery , segmentation , multispectral image , magnetic resonance imaging , nuclear medicine , lesion , contrast (vision) , artificial intelligence , pattern recognition (psychology) , medicine , computer science , radiology , chemistry , pathology , organic chemistry
The aim of this study is to assess the performance of deep learning convolutional neural networks (CNNs) in segmenting gadolinium-enhancing lesions using a large cohort of multiple sclerosis (MS) patients.
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