University of Sussex
Browse

File(s) under permanent embargo

Estimation of large motion in lung CT by integrating regularized keypoint correspondences into dense deformable registration

journal contribution
posted on 2023-06-09, 20:23 authored by Jan Rühaak, Thomas Polzin, Stefan Heldmann, Ivor SimpsonIvor Simpson, Heinz Handels, Jan Modersitzki, Mattias P Heinrich
We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a dense continuous optimization framework. The detection of keypoint correspondences enables robustness against large deformations by jointly optimizing over a large number of potential discrete displacements, whereas the dense continuous registration achieves subvoxel alignment with smooth transformations. Both steps are driven by the same normalized gradient fields data term. We employ curvature regularization and a volume change control mechanism to prevent foldings of the deformation grid and restrict the determinant of the Jacobian to physiologically meaningful values. Keypoint correspondences are integrated into the dense registration by a quadratic penalty with adaptively determined weight. Using a parallel matrix-free derivative calculation scheme, a runtime of about 5 min was realized on a standard PC. The proposed algorithm ranks first in the EMPIRE10 challenge on pulmonary image registration. Moreover, it achieves an average landmark distance of 0.82 mm on the DIR-Lab COPD database, thereby improving upon the state of the art in accuracy by 15. Our algorithm is the first to reach the inter-observer variability in landmark annotation on this dataset.

History

Publication status

  • Published

File Version

  • Published version

Journal

IEEE Transactions on Medical Imaging

ISSN

0278-0062

Publisher

Institute of Electrical and Electronics Engineers

Issue

8

Volume

36

Page range

1746-1757

Department affiliated with

  • Informatics Publications

Research groups affiliated with

  • Data Science Research Group Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2020-01-24

First Compliant Deposit (FCD) Date

2021-01-28