Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility.
Jia YingRenee CattellTianyun ZhaoLan LeiZhao JiangShahid M. HussainYi GaoH.-H. Sherry ChowAlison T. StopeckPatricia A. ThompsonChuan HuangPublished in: Vis. Comput. Ind. Biomed. Art (2022)
Keyphrases
- fully automated
- breast mri
- data driven
- magnetic resonance imaging
- image registration
- manual segmentation
- atlas based segmentation
- fully automatic
- dce mri
- pectoral muscle
- medical imaging
- mri data
- medical images
- breast tissue
- computer aided
- carotid artery
- contrast enhanced
- magnetic resonance images
- computer aided diagnosis
- automated segmentation
- magnetic resonance
- brain tumor segmentation
- deformation field
- medical image analysis
- mr images
- image segmentation
- registration process
- bias field
- completely automated
- atlas construction
- segmentation algorithm
- semi automatic
- phase contrast
- breast cancer
- brain mri
- computed tomography
- anatomical structures
- segmentation method
- image processing
- ct images
- region growing
- brain scans
- image analysis