A novel U-Net approach to segment the cardiac chamber in magnetic resonance images with ghost artifacts.
Ming ZhaoWei YangYu LuKelvin Kian Loong WongPublished in: Comput. Methods Programs Biomed. (2020)
Keyphrases
- magnetic resonance images
- myocardial infarction
- myocardial motion
- cardiac mri
- mr images
- medical images
- mr imaging
- medical imaging
- accurate segmentation
- magnetic resonance imaging
- brain mri
- intra subject
- white matter
- diffusion tensor
- diffusion weighted
- brain tumors
- brain tissue
- patient specific
- high quality
- mri data
- mri images
- manual segmentation
- tissue segmentation
- brain structures
- mri scans
- magnetic resonance
- dynamic range
- partial volume
- multiple sclerosis lesions
- wall motion
- image processing
- shape analysis
- automatic segmentation
- bias field
- beating heart
- machine learning