Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome.
Youngjin YooLisa Y. W. TangDavid K. B. LiLuanne MetzShannon H. KolindAnthony TraboulseeRoger C. TamPublished in: Comput. methods Biomech. Biomed. Eng. Imaging Vis. (2019)
Keyphrases
- multiple sclerosis
- user defined
- deep learning
- magnetic resonance images
- white matter
- clinical trials
- gad enhancing
- brain mri
- lesion segmentation
- mr images
- brain tissue
- magnetic resonance
- data types
- disease progression
- query language
- human brain
- machine learning
- feature space
- corpus callosum
- unsupervised learning
- automatic segmentation
- decision support system
- medical images
- brain images
- anatomical structures
- magnetic resonance imaging
- diffusion tensor imaging
- model selection
- image data
- data structure
- feature extraction