Feasibility of end-to-end trainable two-stage U-Net for detection of axillary lymph nodes in contrast-enhanced CT based on sparse annotations.
Hidir Cem AltunGrzegorz ChlebusColin JacobsHans MeineBram van GinnekenHorst K. HahnPublished in: Medical Imaging: Computer-Aided Diagnosis (2020)
Keyphrases
- lymph nodes
- end to end
- ct data
- contrast enhanced
- computed tomography
- automatic segmentation
- intraoperative
- ct scans
- patient specific
- automatic detection
- ct images
- medical images
- computer tomography
- statistical shape model
- pre operative
- prior information
- image guided
- computer assisted
- x ray
- medical imaging
- lung cancer
- three dimensional
- image reconstruction
- cancer diagnosis
- segmentation algorithm
- clinical applications
- coronary artery
- region of interest
- image data
- statistical analysis
- magnetic resonance