CBCT-to-CT Synthesis for Cervical Cancer Adaptive Radiotherapy via U-Net-Based Model Hierarchically Trained with Hybrid Dataset.
Xi LiuRuijie YangTianyu XiongXueying YangWen LiLiming SongJiarui ZhuMingqing WangJing CaiLisheng GengPublished in: Cancers (2023)
Our model could synthesize CT images with enhanced image quality and accurate HU values. The synthetic CT images preserved the edges of tissues well, which is important for downstream tasks in adaptive radiotherapy.
Keyphrases
- image quality
- computed tomography
- dual energy
- early stage
- deep learning
- convolutional neural network
- locally advanced
- radiation therapy
- optical coherence tomography
- radiation induced
- gene expression
- magnetic resonance imaging
- working memory
- magnetic resonance
- high resolution
- resistance training
- positron emission tomography