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A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis

par Molchanova, Nataliia;Cagol, Alessandro;Ocampo–Pineda, Mario;Lu, Po–Jui;Weigel, Matthias;Chen, Xinjie;Beck, Erin E.S.;Tsagkas, Charidimos;Reich, Daniel S;Bulcke, Colin Vanden;Stölting, Anna;Borrelli, Serena ;Maggi, Pietro ;Lugo, Sebastian Baez;Lemay, Delphine Ribes;Depeursinge, Adrien;Granziera, Cristina;Müller, Henning;Gordaliza, Pedro P.M.;Bach Cuadra, Meritxell
Référence NeuroImage: Clinical, 50, 104007
Publication Publié, 2026-01

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Titre:	A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis
Auteur:	Molchanova, Nataliia; Cagol, Alessandro; Ocampo–Pineda, Mario; Lu, Po–Jui; Weigel, Matthias; Chen, Xinjie; Beck, Erin E.S.; Tsagkas, Charidimos; Reich, Daniel S; Bulcke, Colin Vanden; Stölting, Anna; Borrelli, Serena; Maggi, Pietro; Lugo, Sebastian Baez; Lemay, Delphine Ribes; Depeursinge, Adrien; Granziera, Cristina; Müller, Henning; Gordaliza, Pedro P.M.; Bach Cuadra, Meritxell
Informations sur la publication:	NeuroImage: Clinical, 50, 104007
Statut de publication:	Publié, 2026-01
Sujet CREF:	Neurologie
	Imagerie médicale, radiologie, tomographie
	Cardiologie et circulation
Mots-clés:	Brain
	Cortical lesions
	Deep learning
	Detection
	Magnetic resonance imaging
	Multiple sclerosis
	Segmentation
	Trustworthy AI
Note générale:	SCOPUS: ar.j
Langue:	Anglais
Identificateurs:	urn:issn:2213-1582
	info:doi/10.1016/j.nicl.2026.104007
	info:pii/S2213158226000665
	info:scp/105040630229
	info:pmid/42224860