Daily cone-beam CT multi-organ segmentation for prostate adaptive radiotherapy

Yabo Fu; Yang Lei; Tonghe Wang; Sibo Tian; Pretesh Patel; Ashesh B. Jani; Walter J. Curran; Tian Liu; Xiaofeng Yang

doi:10.1117/12.2580791

15 February 2021 Daily cone-beam CT multi-organ segmentation for prostate adaptive radiotherapy

Yabo Fu, Yang Lei, Tonghe Wang, Sibo Tian, Pretesh Patel, Ashesh B. Jani, Walter J. Curran, Tian Liu, Xiaofeng Yang

Proceedings Volume 11596, Medical Imaging 2021: Image Processing; 1159620 (2021) https://doi.org/10.1117/12.2580791
Event: SPIE Medical Imaging, 2021, Online Only

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Abstract

Adaptive radiotherapy which relies on patient Cone-Beam CT (CBCT) imaged right before dose delivery to update the contouring and treatment plans has the potential to increase dose delivery accuracy and improve treatment outcomes. In this study, we proposed a synthetic MRI-aided multi-organ segmentation from cone-beam CT for prostate adaptive radiotherapy. A cycle-consistent generative adversarial network (CycleGAN) was first trained with pre-aligned CBCT and MRI image pairs to generate sMRI based on given CBCT image. Feature maps were then extracted from CBCT and sMRI separately using two different U-Nets. The feature maps were combined using attention gates and input to CNN to predict the final segmentation of these critical structures. The segmentation results were evaluated using 100 patients’ datasets. The Dice similarity coefficient (DSC) was 0.96±0.03, 0.91±0.08, 0.93±0.04, 0.95±0.05, and 0.95±0.05 for bladder, prostate, rectum, left femoral head (LFH) and right femoral head (RFH), respectively.

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Citation Download Citation

Yabo Fu, Yang Lei, Tonghe Wang, Sibo Tian, Pretesh Patel, Ashesh B. Jani, Walter J. Curran, Tian Liu, and Xiaofeng Yang "Daily cone-beam CT multi-organ segmentation for prostate adaptive radiotherapy", Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 1159620 (15 February 2021); https://doi.org/10.1117/12.2580791

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