CT guided material decomposition of spectral CBCT

Qian Wang; Huiqiao Xie; Tonghe Wang; Justin Roper; Xiangyang Tang; Jeffrey D. Bradley; Tian Liu; Xiaofeng Yang

doi:10.1117/12.2611162

4 April 2022 CT guided material decomposition of spectral CBCT

Qian Wang, Huiqiao Xie, Tonghe Wang, Justin Roper, Xiangyang Tang, Jeffrey D. Bradley, Tian Liu, Xiaofeng Yang

Proceedings Volume 12031, Medical Imaging 2022: Physics of Medical Imaging; 1203128 (2022) https://doi.org/10.1117/12.2611162
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

Cone-beam CT (CBCT) plays a crucial role in modern image-guided radiotherapy for patient setup and verification. However, the image quality of CBCT is inferior to that of CT in terms of HU accuracy, image artifact, and tissue contrast, which impedes the potential of CBCT in further radiotherapy applications, such as online contouring and dose calculation for adaptive radiotherapy. In this work, we propose an optimization model for material decomposition of spectral CBCT, which innovatively incorporates CT as guidance to simultaneously improve the image quality and material composition of CBCT images. Both phantom and patient studies demonstrate the effectiveness and superiority of the proposed method in noise and artifact removal, decomposition-accuracy maintenance, etc.

Citation Download Citation

Qian Wang, Huiqiao Xie, Tonghe Wang, Justin Roper, Xiangyang Tang, Jeffrey D. Bradley, Tian Liu, and Xiaofeng Yang "CT guided material decomposition of spectral CBCT", Proc. SPIE 12031, Medical Imaging 2022: Physics of Medical Imaging, 1203128 (4 April 2022); https://doi.org/10.1117/12.2611162

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