Fully automated segmentation of lumbar bone marrow in sagittal, high-resolution T1-weighted magnetic resonance images using 2D U-NET.
Eo-Jin HwangSanghee KimJoon-Yong JungPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- magnetic resonance images
- fully automated
- brain mri
- high resolution
- fully automatic
- corpus callosum
- brain tissue
- mr images
- mri data
- bone marrow
- medical images
- partial volume
- mr imaging
- manual segmentation
- brain scans
- brain tumors
- tissue segmentation
- medical imaging
- multiple sclerosis lesions
- white matter
- bias field
- brain structures
- accurate segmentation
- magnetic resonance imaging
- brain mr images
- automated segmentation
- diffusion tensor
- intensity distribution
- gray matter
- semi automatic
- brain tumor segmentation
- stem cell
- remote sensing
- image segmentation
- segmentation algorithm
- medical image analysis
- diffusion weighted
- image intensity
- level set
- partial volume effects
- high quality
- super resolution
- magnetic resonance
- segmentation method
- mr brain images
- diffusion tensor imaging