IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI.
Ziyun LiangXiaoqing GuoJ. Alison NobleKonstantinos KamnitsasPublished in: CoRR (2024)
Keyphrases
- tissue segmentation
- multiple sclerosis
- brain mri
- brain scans
- brain structures
- brain tumors
- magnetic resonance images
- mri scans
- breast mri
- pet images
- medical images
- mr images
- mri brain
- probabilistic atlas
- brain tissue
- lesion segmentation
- magnetic resonance imaging
- brain atlas
- grey matter
- model based segmentation
- medical imaging
- partial volume
- brain mr images
- mri data
- mri images
- brain images
- corpus callosum
- gray matter
- human brain
- caudate nucleus
- brain imaging
- cerebrospinal fluid
- white matter
- magnetic resonance
- brain anatomy
- partial volume effects
- computer aided diagnosis
- brain mapping
- anatomical structures
- bias field
- intensity distribution
- imaging modalities
- medical image analysis
- segmentation algorithm
- anomaly detection
- level set
- image segmentation
- intra subject
- brain tumor segmentation
- dce mri
- fully unsupervised
- accurate segmentation
- region growing
- segmentation method
- image analysis
- brain segmentation
- subcortical structures
- cortical thickness
- atlas based segmentation
- positron emission tomography
- carotid artery
- mouse brain
- image registration
- high resolution