Segmentation of male pelvic organs on computed tomography with a deep neural network fine-tuned by a level-set method.
Gonçalo AlmeidaAna Rita FigueiraJoana LencartJoão Manuel R. S. TavaresPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- computed tomography
- level set method
- medical imaging
- image segmentation
- medical images
- level set
- neural network
- ct images
- fine tuned
- ct scans
- deformable models
- ct data
- medical image segmentation
- level set evolution
- medical image processing
- segmentation result
- anatomical structures
- active contours
- energy functional
- piecewise constant
- segmentation algorithm
- liver segmentation
- fine tuning
- mr images
- shape prior
- image analysis
- computer aided diagnosis
- soft tissue
- imaging modalities
- x ray
- ct imaging
- multiscale
- segmentation method
- image processing
- curve evolution
- computer vision
- magnetic resonance
- accurate segmentation
- fracture detection
- partial differential equations
- image guided
- active contour model
- region growing
- region of interest
- image reconstruction
- pattern recognition
- three dimensional
- manual segmentation
- clinical applications
- numerical methods
- markov random field
- domain specific
- optical flow
- pet ct