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

Published

Conference Paper

© 2014 IEEE. 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.

Duke Authors

Cited Authors

  • Zhong, H; Cai, J; Glide-Hurst, C; Chetty, IJ

Published Date

  • January 1, 2014

Published In

  • 2014 Ieee 11th International Symposium on Biomedical Imaging, Isbi 2014

Start / End Page

  • 770 - 773

International Standard Book Number 13 (ISBN-13)

  • 9781467319591

Citation Source

  • Scopus