Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching

Youngjun Kim, Yong Hum Na, Lei Xing, Rena Lee, Sehyung Park

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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±1.88 mm to 0.57±0.66 mm. We demonstrate the effectiveness of the proposed method by presenting some medical applications.

Original languageEnglish
Pages (from-to)173-181
Number of pages9
JournalComputers in Biology and Medicine
Volume77
DOIs
StatePublished - 1 Oct 2016

Keywords

  • Automatic correspondence
  • Deformable registration
  • Mesh deformation
  • Radial basis function
  • Robust point matching

Fingerprint

Dive into the research topics of 'Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching'. Together they form a unique fingerprint.

Cite this