Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks

The quantification of new or enlarged lesions from follow-up MRI scans is an important surrogate of clinical disease activity in patients with multiple sclerosis (MS). Not only is manual segmentation time consuming, but inter-rater variability is high. Currently, only a few fully automated methods a...

Descripción completa

Detalles Bibliográficos
Autores principales: Krüger, Julia, Opfer, Roland, Gessert, Nils, Ostwaldt, Ann-Christin, Manogaran, Praveena, Kitzler, Hagen H., Schlaefer, Alexander, Schippling, Sven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554211/
https://www.ncbi.nlm.nih.gov/pubmed/33038667
http://dx.doi.org/10.1016/j.nicl.2020.102445

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554211/
https://www.ncbi.nlm.nih.gov/pubmed/33038667
http://dx.doi.org/10.1016/j.nicl.2020.102445

Ejemplares similares