An adaptive finite element method to cope with a large scale lung deformation in magnetic resonance images

Hualiang Zhong, Jing Cai, Carri Glide-Hurst, Indrin J. Chetty

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


The purpose of this study is to present an adaptive deformable image registration method to improve the performance of a multi-resolution "demons" registration algorithm in handling large scale lung deformation observed in 4D-MR images. Specifically, a finite element method (FEM) was integrated with MR tagging information to correct registration errors in the lung region. The displacements of 349 tagged grids were calculated with an average of 3.5 cm. The mean error of the demons registration over the tags was 2.5 cm which was reduced to 0.7 cm by the FEM registration. The FEM-generated transformation was merged to the demons deformation map without introducing any discontinuity. This method can help correct deformable registration errors identified in the clinical setting.
Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Number of pages4
ISBN (Electronic)9781467319591
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Renaissance Beijing Capital Hotel, Beijing, China
Duration: 29 Apr 20142 May 2014


Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014


  • 4D-magnetic resonance image
  • Adaptive image registration
  • Finite element method
  • Grid of MR Tags

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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