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.
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