Unsupervised CBCT quality improvement for quantitative image analysis in radiotherapy using patient-specific score-based prior

In current image-guided radiotherapy (IGRT) protocols, cone-beam CT (CBCT) scans are routinely performed on a daily or weekly basis, which is an ideal imaging modality for quantitative medical image analysis tasks, including the delta radiomics and monitoring of tumor response and anatomical change. However, compared to diagnostic fan-beam CT images, CBCT images are corrupted by significant artifacts, including streaking, cupping, shading, and scatter contamination, leading to inaccurate Hounsfield unit (HU) measurements. Such issues limit the quantitative utilization of CBCT images and impede the practice of CBCT-based radiomics. To improve the image quality of CBCT for quantitative image analysis in radiotherapy, such as segmentation and delta radiomics, we develop an unsupervised method for CBCT correction using the patient-specific score-based image prior.