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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...
Autores principales: | Krüger, Julia, Opfer, Roland, Gessert, Nils, Ostwaldt, Ann-Christin, Manogaran, Praveena, Kitzler, Hagen H., Schlaefer, Alexander, Schippling, Sven |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
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 |
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