Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

[Automatic Delineation of Clinical Target Volume and Organ at Risk by Deep Learning for Prostate Cancer Adaptive Radiotherapy].

In Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation

Adaptive radiotherapy can modify the treatment plan online based on the clinical target volume (CTV) and organ at risk (OAR) contours on the cone-beam CT (CBCT) before treatment, improving the accuracy of radiotherapy. However, manual delineation of CTV and OAR on CBCT is time-consuming. In this study, a deep neural network-based method based on U-Net was purposed. CBCT images and corresponding mask were used for model training and validation, showing superior performance in terms of the segmentation accuracy. The proposed method could be used in the clinic to support rapid CTV and OAR contouring for prostate adaptive radiotherapy.

Song Xinyu, Zhang Xiangyu, Li Jing, Liang Lan, Yang Yang, Li Guangjun, Bai Sen

2022-Nov-30

U-Net, cone-beam CT, multi-organ delineation, prostate cancer