Unsupervised CBCT quality improvement for quantitative image analysis in radiotherapy using patient-specific score-based prior Conference Paper
| Authors: | Peng, J.; Gao, Y.; Chang, C. W.; Safari, M.; Qiu, R.; Wang, T.; Kesarwala, A.; Yu, D.; Yang, X. |
| Title: | Unsupervised CBCT quality improvement for quantitative image analysis in radiotherapy using patient-specific score-based prior |
| Conference Title: | Medical Imaging 2025: Computer-Aided Diagnosis |
| Abstract: | 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. © 2025 SPIE. |
| Keywords: | radiotherapy; diagnostic radiography; quality improvement; quantitative image analysis; image guided radiotherapy; cone-beam ct; imaging modality; ct-scan; patient specific; image correlation; medical image analysis; cone beam ct images; photointerpretation; current image |
| Journal Title | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
| Volume: | 13407 |
| Conference Dates: | 2025 Feb 17-20 |
| Conference Location: | San Diego, CA |
| ISBN: | 1605-7422 |
| Publisher: | SPIE |
| Date Published: | 2025-01-01 |
| Start Page: | 134072S |
| Language: | English |
| DOI: | 10.1117/12.3047160 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference paper (ISBN: 9781510685925) -- Source: Scopus |
