Comparing lesion segmentation methods in multiple sclerosis: Input from one manually delineated subject is sufficient for accurate lesion segmentation

PURPOSE: Accurate lesion segmentation is important for measurements of lesion load and atrophy in subjects with multiple sclerosis (MS). International MS lesion challenges show a preference of convolutional neural networks (CNN) strategies, such as nicMSlesions. However, since the software is traine...

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Detalles Bibliográficos
Autores principales: Weeda, M.M., Brouwer, I., de Vos, M.L., de Vries, M.S., Barkhof, F., Pouwels, P.J.W., Vrenken, H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861662/
https://www.ncbi.nlm.nih.gov/pubmed/31734527
http://dx.doi.org/10.1016/j.nicl.2019.102074

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861662/
https://www.ncbi.nlm.nih.gov/pubmed/31734527
http://dx.doi.org/10.1016/j.nicl.2019.102074

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