Automated left and right ventricular chamber segmentation in cardiac magnetic resonance images using dense fully convolutional neural network.
Marco PensoSara MocciaStefano ScafuriGiuseppe MuscogiuriGianluca PontoneMauro PepiEnrico Gianluca CaianiPublished in: Comput. Methods Programs Biomed. (2021)
Keyphrases
- magnetic resonance images
- myocardial infarction
- brain mri
- convolutional neural network
- medical images
- cardiac mri
- partial volume
- brain scans
- intra subject
- mr images
- brain tumors
- mri data
- tissue segmentation
- mri images
- medical imaging
- mr imaging
- multiple sclerosis lesions
- blood pool
- brain structures
- white matter
- bias field
- mri scans
- brain tissue
- left ventricle
- magnetic resonance imaging
- myocardial motion
- high resolution
- accurate segmentation
- cerebrospinal fluid
- manual segmentation
- gray matter
- brain tumor segmentation
- face detection
- diffusion tensor
- brain mr images
- partial volume effects
- left ventricular
- medical image analysis
- magnetic resonance
- fully automatic
- level set
- image segmentation
- anatomical structures
- intensity distribution
- segmentation method
- region growing
- segmentation algorithm
- diffusion weighted
- automatically segmenting
- patient specific