Synthetic CT generation from CBCT images via deep learning

• DOI: 10.1002/mp.13978
• Publication Date: 2019-12-19T06:11:16Z
• Authors: Liyuan Chen; Xiao Liang; Chenyang Shen; Steve Jiang; Jing Wang
• Keywords: Image-guided radiation therapy

Cone-beam computed tomography (CBCT) scanning is used daily or weekly (i.e., on-treatment CBCT) for accurate patient setup in image-guided radiotherapy. However, inaccuracy of CT numbers prevents CBCT from performing advanced tasks such as dose calculation and treatment planning. Motivated by the promising performance deep learning medical imaging, we propose a U-net-based approach that synthesizes CT-like images with planning CT, while keeping same anatomical structure CBCT.