CNN-based hierarchical coarse-to-fine segmentation of pelvic CT images for prostate cancer radiotherapy.
Sharmin SultanaAdam RobinsonDaniel Y. SongJunghoon LeePublished in: Medical Imaging: Image-Guided Procedures (2020)
Keyphrases
- coarse to fine
- ct images
- prostate cancer
- medical images
- radiation therapy
- medical imaging
- treatment planning
- medical image analysis
- image registration
- mr images
- fracture detection
- multiscale
- image guided
- pet ct
- computed tomography
- bone segmentation
- ct scans
- computer aided
- radiotherapy treatment
- active shape model
- multiresolution
- accurate segmentation
- cancer patients
- automated segmentation
- anatomical structures
- image segmentation
- imaging modalities
- magnetic resonance
- region of interest
- prostate segmentation
- object detection
- magnetic resonance images
- treatment plan
- dce mri
- traumatic pelvic
- deformable registration
- normal tissue
- clinical applications
- segmentation result
- soft tissue
- lymph nodes
- segmentation method
- respiratory motion
- image analysis
- segmentation algorithm
- deformable models
- magnetic resonance imaging
- computer aided diagnosis
- brain tumors
- manual segmentation
- x ray images
- medical data
- energy function
- x ray
- multi class
- machine learning