ArticleComputers in biology and medicine2016
Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching.
Article in Computers in biology and medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.PloS one · 2020Observational
- Anisotropic non-rigid Iterative Closest Point Algorithm for respiratory motion abdominal surface matching.Biomedical engineering online · 2019Article
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5 authors.
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Abstract
Deformable surface mesh registration is a useful technique for various medical applications, such as intra-operative treatment guidance and intra- or inter-patient study. In this paper, we propose an automatic deformable mesh registration technique. The proposed method iteratively deforms a source mesh to a target mesh without manual feature extraction. Each iteration of the registration consists of two steps, automatic correspondence finding using robust point-matching (RPM) and local deformation using a radial basis function (RBF). The proposed RBF-based RPM algorithm solves the interlocking problems of correspondence and deformation using a deterministic annealing framework with fuzzy correspondence and RBF interpolation. Simulation tests showed promising results, with the average deviations decreasing by factors of 21.2 and 11.9, respectively. In the human model test, the average deviation decreased from 1.72±1.88mm to 0.57±0.66mm. We demonstrate the effectiveness of the proposed method by presenting some medical applications.
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