Prediction of post-radiotherapy recurrence volumes in head and neck squamous cell carcinoma using 3D U-Net segmentation.
Denis KutnárIvan Richter VogeliusKatrin Elisabet HåkanssonJens PetersenJeppe FriborgLena SpechtMogens BernsdorfAnita GothelfClaus KristensenAbraham George SmithPublished in: CoRR (2023)
Keyphrases
- cell nuclei
- lung cancer
- cancer cells
- lymph nodes
- cell segmentation
- automated detection
- fluorescence microscopy images
- prediction accuracy
- microscope images
- microscopy images
- image segmentation
- cancer diagnosis
- level set
- microscopic images
- segmentation algorithm
- prediction model
- quantitative analysis
- low contrast
- medical images
- multiscale
- segmentation method
- cell nucleus
- confocal images
- automated analysis
- early detection
- treatment planning
- prostate cancer
- fully automatic
- phase contrast
- image analysis
- three dimensional
- accurate segmentation
- prediction error
- shape prior
- region growing
- image volumes
- white blood cells
- face recognition
- image sequences