Anatomical and Diagnostic Bayesian Segmentation in Prostate MRI - Should Different Clinical Objectives Mandate Different Loss Functions?
Anindo SahaJoeran BosmaJasper LinmansMatin HosseinzadehHenkjan J. HuismanPublished in: CoRR (2021)
Keyphrases
- loss function
- medical images
- brain scans
- brain structures
- mr imaging
- clinical applications
- magnetic resonance imaging
- anatomical structures
- probabilistic atlas
- brain atlas
- brain mri
- automatic segmentation
- intra subject
- mr images
- medical imaging
- magnetic resonance images
- squared error
- pairwise
- medical image analysis
- learning to rank
- loss minimization
- risk minimization
- prostate cancer
- imaging modalities
- magnetic resonance
- manual segmentation
- logistic regression
- accurate segmentation
- mouse brain
- support vector
- treatment planning
- segmentation algorithm
- brain tumors
- atlas construction
- mri data
- prostate segmentation
- convex loss functions
- reproducing kernel hilbert space
- level set
- segmentation method
- brain images
- ct images
- ultrasound images
- maximum likelihood
- deformable models
- human brain
- carotid artery
- bayesian networks
- shape analysis
- image segmentation
- maximum entropy
- atlas based segmentation
- inter subject
- radiation therapy
- graph cuts
- bregman divergences
- automated segmentation
- multi class
- clinical trials