Shallow vs Deep Learning Architectures for White Matter Lesion Segmentation in the Early Stages of Multiple Sclerosis-Reference-Cited by-同舟云学术

Shallow vs Deep Learning Architectures for White Matter Lesion Segmentation in the Early Stages of Multiple Sclerosis

Published:2019 Issue: Volume: Page:142-151
ISSN:0302-9743
Container-title:Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
language:
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Author:

La Rosa Francesco,Fartaria Mário João,Kober Tobias,Richiardi Jonas,Granziera Cristina,Thiran Jean-Philippe,Cuadra Meritxell Bach

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-11723-8_14

Reference25 articles.

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3. Carass, A., et al.: Longitudinal multiple sclerosis lesion segmentation: resource and challenge. NeuroImage 148, 77–102 (2017)

4. Commowick, O., Cervenansky, F., Ameli, R.: MSSEG challenge proceedings: multiple sclerosis lesions segmentation challenge using a data management and processing infrastructure. In: MICCAI 2016 (2016)

5. Valverde, S., et al.: Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach. NeuroImage 155, 159–168 (2017)

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