Cone Beam Computed Tomography Image-Quality Improvement Using "One-Shot" Super-resolution.

ABSTRACT: Cone beam computed tomography (CBCT) images are convenient representations for obtaining information about patients' internal organs, but their lower image quality than those of treatment planning CT images constitutes an important shortcoming. Several proposed CBCT image-quality improvement methods based on deep learning require large amounts of training data. Our newly developed model using a super-resolution method, "one-shot" super-resolution (OSSR) based on the "zero-shot" super-resolution method, requires only small amounts of training data to improve CBCT image quality using only the target CBCT image and the paired treatment planning CT image. For this study, pelvic CBCT images and treatment planning CT images of 30 prostate cancer patients were used. We calculated the root mean sq

SUBMITTER: Tsuji T 

PROVIDER: S-EPMC12344046 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature