Fully automated intracranial ventricle segmentation on CT with 2D regional convolutional neural network to estimate ventricular volume.
Trevor J. HuffParker E. LudwigDavid SalazarJustin A. CramerPublished in: Int. J. Comput. Assist. Radiol. Surg. (2019)
Keyphrases
- fully automated
- cerebrospinal fluid
- fully automatic
- left ventricle
- blood pool
- convolutional neural network
- white matter
- image slices
- mri data
- medical images
- semi automated
- mr images
- partial volume effects
- gray matter
- semi automatic
- airway tree
- magnetic resonance images
- ct scans
- brain mr images
- manual segmentation
- medical imaging
- face detection
- computer tomography
- completely automated
- left ventricular
- mri images
- image volumes
- image segmentation
- distance maps
- computed tomography
- magnetic resonance
- ct volume
- automated segmentation
- x ray
- ct images
- low contrast
- ground truth
- level set
- image reconstruction
- magnetic resonance imaging
- medical image analysis
- deformable models
- region growing
- segmentation algorithm
- human brain
- computer aided diagnosis
- neural network