Scribble-guided dose prediction uses a completion module with supervoxel regularization to generate dense masks from sparse labels and conditions a dose network on them, achieving strong performance on the GDP-HMM dataset with lower annotation cost.
In: International Conference on Medical Image Computing and Computer-Assisted Intervention
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ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy
Scribble-guided dose prediction uses a completion module with supervoxel regularization to generate dense masks from sparse labels and conditions a dose network on them, achieving strong performance on the GDP-HMM dataset with lower annotation cost.
- Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-Guided Subtyping and Lesion-Wise Model Ensemble