SSL^2: Self-Supervised Learning meets Semi-Supervised Learning: Multiple Sclerosis Segmentation in 7T-MRI from large-scale 3T-MRI.
Jiacheng WangHao LiHan LiuDewei HuDaiwei LuKeejin YoonKelsey BarterFrancesca BagnatoIpek OguzPublished in: CoRR (2023)
Keyphrases
- semi supervised learning
- brain mri
- supervised learning
- multiple sclerosis
- magnetic resonance images
- unsupervised learning
- labeled and unlabeled data
- medical images
- semi supervised
- active learning
- labeled data
- unlabeled data
- graph based semi supervised learning
- learning tasks
- mr images
- white matter
- learning algorithm
- magnetic resonance imaging
- mri data
- learning process
- co training
- lesion segmentation
- machine learning
- domain adaptation
- kernel machines
- image segmentation
- magnetic resonance
- medical imaging
- training data
- computer vision
- semi supervised learning setting
- anatomical structures
- high resolution
- brain tissue
- energy function
- feature selection
- data sets