Lijuan Zhang1, Yu Zhou2, Jiawei Tian3,*, Fupei Guo4, Xiang Zhang4, Bo Yang4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3949-3968, 2025, DOI:10.32604/cmes.2025.071869
- 23 December 2025
Abstract In endoscopic surgery, the limited field of view and the nonlinear deformation of organs caused by patient movement and respiration significantly complicate the modeling and accurate tracking of soft tissue surfaces from endoscopic image sequences. To address these challenges, we propose a novel Hybrid Triangular Matching (HTM) modeling framework for soft tissue feature tracking. Specifically, HTM constructs a geometric model of the detected blobs on the soft tissue surface by applying the Watershed algorithm for blob detection and integrating the Delaunay triangulation with a newly designed triangle search segmentation algorithm. By leveraging barycentric coordinate theory, More >