A deep learning-based framework (Co-ReTr) for auto-segmentation of non-small cell-lung cancer in computed tomography images.
Tenzin KunkyabZhila BahramiHeqing ZhangZheng LiuDerek HydePublished in: Journal of applied clinical medical physics (2024)
Our deep learning framework, based on CNN and transformer, performs auto-segmentation efficiently and could potentially assist clinical radiotherapy workflow.
Keyphrases
- deep learning
- convolutional neural network
- computed tomography
- artificial intelligence
- early stage
- machine learning
- positron emission tomography
- radiation therapy
- magnetic resonance imaging
- locally advanced
- radiation induced
- electronic health record
- magnetic resonance
- squamous cell carcinoma
- image quality
- dual energy
- optical coherence tomography
- pet ct