Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes.
Junhao WenErdem VarolAristeidis SotirasZhijian YangGanesh B. ChandGüray ErusHaochang ShouAhmed AbdulkadirGyujoon HwangDominic B. DwyerAlessandro PigoniPaola DazzanRené S. KahnHugo G. SchnackMarcus V. ZanettiEva MeisenzahlGeraldo F. BusattoBenedicto Crespo-FacorroRomero-Garcia RafaelChristos PantelisStephen J. WoodChuanjun ZhuoRussell T. ShinoharaYong FanRuben C. GurRaquel E. GurTheodore D. SatterthwaiteNikolaos KoutsoulerisDaniel H. WolfChristos DavatzikosPublished in: Medical Image Anal. (2022)
Keyphrases
- brain images
- semi supervised clustering
- multiscale
- mild cognitive impairment
- semi supervised
- medical images
- metric learning
- unsupervised clustering
- magnetic resonance
- pairwise constraints
- human brain
- background knowledge
- white matter
- semi supervised learning
- semi supervised classification
- image representation
- nonnegative matrix factorization
- k means
- clustering algorithm
- image segmentation
- labeled data
- natural images
- document clustering
- human subjects
- image processing
- computer vision
- image data
- magnetic resonance imaging
- breast cancer
- mr images
- supervised learning
- ground truth
- early diagnosis