Correspondence-free local-to-global liver deformation correction via implicit neural representation and biomechanical model.

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Bibliographic Details
Title: Correspondence-free local-to-global liver deformation correction via implicit neural representation and biomechanical model.
Authors: Yang X; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.; University of Chinese Academy of Sciences, Beijing, China., Yang Z; Multi-scale Medical Robotics Center, Chinese University of Hong Kong, Hong Kong, China., Huang B; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.; University of Chinese Academy of Sciences, Beijing, China., Wang Y; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.; College of Information Science and Engineering, Northeastern University, Shenyang, China., Luo H; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.; School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, China., Sun X; School of Computer and Artificial Intelligence, Foshan University, Foshan, China., Jia F; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. fc.jia@siat.ac.cn.; Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. fc.jia@siat.ac.cn.; State Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China. fc.jia@siat.ac.cn.
Source: International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2026 Jun 29. Date of Electronic Publication: 2026 Jun 29.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: Germany NLM ID: 101499225 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1861-6429 (Electronic) Linking ISSN: 18616410 NLM ISO Abbreviation: Int J Comput Assist Radiol Surg Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1861-6429
DOI:10.1007/s11548-026-03737-6