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Intensity‐based 2D‐3D registration for an ACL reconstruction navigation system
Author(s) -
Guo Na,
Yang Biao,
Ji Xuquan,
Wang Yuhan,
Hu Lei,
Wang Tianmiao
Publication year - 2019
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.2008
Subject(s) - computer vision , computer science , artificial intelligence , mutual information , anterior cruciate ligament , navigation system , similarity (geometry) , anterior cruciate ligament reconstruction , medicine , surgery , image (mathematics)
To improve the positioning accuracy of tunnels for anterior cruciate ligament (ACL) reconstruction, we proposed an intensity‐based 2D‐3D registration method for an ACL reconstruction navigation system. Methods for digitally reconstructed radiograph (DRR) generation, similarity measurement, and optimization are crucial to 2D‐3D registration. We evaluated the accuracy, success rate, and processing time of different methods: (a) ray‐casting and splating were compared for DRR generation; (b) normalized mutual information (NMI), Mattes mutual information (MMI), and Spearman's rank correlation coefficient (SRC) were assessed for similarity between registrations; and (c) gradient descent (GD) and downhill simplex (DS) were compared for optimization. The combination of splating, SRC, and GD provided the best composite performance and was applied in an augmented reality (AR) ACL reconstruction navigation system. The accuracy of the navigation system could fulfill the clinical needs of ACL reconstruction, with an end pose error of 2.50 mm and an angle error of 2.74°.