An automatic congenital radio-ulnar synostosis deformity evaluation method (CRUS-DE): integrating TLT-SAM and GPMM-R for landmark identification.

ABSTRACT: Congenital Radio-Ulnar Synostosis (CRUS) causes difficulty in forearm rotation, which is treated using osteotomy. Effective preoperative planning of osteotomy requires automatic and objective quantification of deformity angles. In this paper, an automatic Congenital Radio-Ulnar Synostosis deformity evaluation method (CRUS-DE) is proposed. Initially, a method using threshold-layer tracking (TLT) and the segment anything model (SAM) is designed to recognize and segment the forearm from CT images. Subsequently, the Gaussian Process Morphable Model, in conjunction with refinement based on anatomical characteristics is developed to accurately identify forearm landmarks. Finally, the model automatically estimates deformity angles for quantitative assessment of CRUS. The forearm landmarks and def

SUBMITTER: Liu L 

PROVIDER: S-EPMC12910016 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature