Towards personalized biomechanical model and MIND-weighted point matching for robust deformable MR-TRUS registration

Yi Wang, Dong Ni, Jing Qin, Muqing Lin, Xiaoyan Xie, Ming Xu, Pheng Ann Heng

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

2 Citations (Scopus)

Abstract

This paper explores a novel deformable MR-TRUS registration method, which uses a personalized statistical motion model and a robust point matching strategy that is boosted by the modality independent neighborhood descriptor (MIND) algorithm. Current deformable MR-TRUS registration methods limit to inaccurate deformation estimation and unstable point correspondence. To precisely estimate tissue deformation, we construct a personalized statistical motion model (PSMM) on the basis of finite element methods and patient-specific biomechanical properties that were detected by ultrasound elastography. To accurately obtain the point correspondence between surface point sets segmented from MR and TRUS images, we first adopt the PSMM to provide realistic boundary conditions for point correspondence estimation. We further introduce the MIND to weight a robust point matching procedure. We evaluate our method on five datasets from volunteers. The experimental results demonstrate that our novel approach provides more accurate and robust MR-TRUS registration than state-of-the-art methods. The current target registration error was significantly improved from 2.6 to 1.8 mm. which completely meets the clinical requirement of less than 2.5 mm.
Original languageEnglish
Title of host publicationComputer-Assisted and Robotic Endoscopy - 1st International Workshop, CARE 2014 held in Conjunction with MICCAI 2014, Revised Selected Papers
PublisherSpringer Verlag
Pages121-130
Number of pages10
ISBN (Electronic)9783319134093
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8899
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Deformable registration
  • Elastography
  • MIND
  • MR-TRUS prostate registration
  • Robust point matching
  • Statisticalmotionmodel

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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