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Found 4 papers, 0 papers with code
Dcl-Net: Dual Contrastive Learning Network for Semi-Supervised Multi-Organ Segmentation
Semi-supervised learning is a sound measure to relieve the strict demand of abundant annotated datasets, especially for challenging multi-organ segmentation .
Triplet-constraint Transformer with Multi-scale Refinement for Dose Prediction in Radiotherapy
Radiotherapy is a primary treatment for cancers with the aim of applying sufficient radiation dose to the planning target volume (PTV) while minimizing dose hazards to the organs at risk (OARs).
Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encoding
In the forward process, DiffDose transforms dose distribution maps into pure Gaussian noise by gradually adding small noise and a noise predictor is simultaneously trained to estimate the noise added at each timestep.
DiffDP: Radiotherapy Dose Prediction via a Diffusion Model
To alleviate this limitation, we innovatively introduce a diffusion-based dose prediction (DiffDP) model for predicting the radiotherapy dose distribution of cancer patients.
