Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks.
Liesbeth VandewinckeleSiri WillemsDavid RobbenJulie Van Der VeenWouter CrijnsSandra NuytsFrederik MaesPublished in: Comput. methods Biomech. Biomed. Eng. Imaging Vis. (2020)
Keyphrases
- ct scans
- organ segmentation
- abdominal organs
- lymph nodes
- medical images
- convolutional neural networks
- rigid registration
- computed tomography
- medical imaging
- ct images
- automated segmentation
- ct data
- x ray
- computed tomography images
- computer tomography
- registration accuracy
- ct imaging
- computer aided diagnosis
- deformable models
- liver segmentation
- region of interest
- computer aided detection
- registration process
- level set
- medical image analysis
- fracture detection
- image registration
- medical image processing
- anatomical structures
- convolutional network
- bone segmentation
- segmentation method
- computer aided
- pairwise
- computer vision
- high quality
- pattern recognition
- image analysis
- automatic segmentation
- imaging modalities
- segmentation algorithm
- mr images
- video sequences
- multiscale
- x ray images
- feature extraction