LMU University Hospital Researchers Update Understanding of Radiation Oncology (Minimum imaging dose for deep learning-based pelvic synthetic computed tomography generation from cone beam images).

Researchers at LMU University Hospital in Munich, Germany have conducted a study on radiation oncology, specifically focusing on the use of cone-beam computed tomography (CBCT) in image-guided radiotherapy. The study aimed to identify the lowest achievable imaging dose while maintaining image quality. Two deep learning algorithms, cycle generative adversarial network (cycleGAN) and contrastive unpaired translation network (CUT), were used to generate synthetic computed tomography (sCT) from reduced imaging dose CBCTs. The study found that sCTs based on a 25% imaging dose achieved the minimum imaging dose while maintaining segmentation accuracy. The research was published in the journal Physics and Imaging in Radiation Oncology. [Extracted from the article]