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A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs

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journal contribution
posted on 21.09.2018, 14:08 by Lianghao Han, Hua Dong, Jamie R. McClelland, Liangxiu Han, David J. Hawkes, Dean C. Barratt
This paper presents a new hybrid biomechanical model-based non-rigid image registration method for lung motion estimation. In the proposed method, a patient-specific biomechanical modelling process captures major physically realistic deformations with explicit physical modelling of sliding motion, whilst a subsequent non-rigid image registration process compensates for small residuals. The proposed algorithm was evaluated with 10 4D CT datasets of lung cancer patients. The target registration error (TRE), defined as the Euclidean distance of landmark pairs, was significantly lower with the proposed method (TRE = 1.37 mm) than with biomechanical modelling (TRE = 3.81 mm) and intensity-based image registration without specific considerations for sliding motion (TRE = 4.57 mm). The proposed method achieved a comparable accuracy as several recently developed intensity-based registration algorithms with sliding handling on the same datasets. A detailed comparison on the distributions of TREs with three non-rigid intensity-based algorithms showed that the proposed method performed especially well on estimating the displacement field of lung surface regions (mean TRE = 1.33 mm, maximum TRE = 5.3 mm). The effects of biomechanical model parameters (such as Poisson’s ratio, friction and tissue heterogeneity) on displacement estimation were investigated. The potential of the algorithm in optimising biomechanical models of lungs through analysing the pattern of displacement compensation from the image registration process has also been demonstrated.

Funding

The authors would like to acknowledge the financial support from EPSRC program Grant EP/F025750/1 and EP/H046410. The work is also sponsored by Shanghai Pujiang Program (16PJ1409400).

History

School

  • Science

Department

  • Computer Science

Published in

Medical Image Analysis

Volume

39

Pages

87 - 100

Citation

HAN, L. ... et al, 2017. A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs. Medical Image Analysis, 39, pp.87-100.

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

11/04/2017

Publication date

2017-04-19

Notes

This paper was published in the journal Medical Image Analysis and the definitive published version is available at https://doi.org/10.1016/j.media.2017.04.003.

ISSN

1361-8415

Language

en

Exports