UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Statistical Motion Mask and Sliding Registration

Eiben, B; Tran, EH; Menten, MJ; Oelfke, U; Hawkes, DJ; McClelland, JR; (2018) Statistical Motion Mask and Sliding Registration. In: Klein, S and Staring, M and Durrleman, S and Sommer, S, (eds.) Proceedings: Biomedical Image Registration. (pp. pp. 13-23). Springer Nature: Cham, Switzerland. Green open access

[img]
Preview
Text
Eiben_Statistical motion mask and sliding registration_AAM.pdf - Accepted version

Download (4MB) | Preview

Abstract

Accurate registration of images depicting respiratory motion, e.g. 4DCT or 4DMR, can be challenging due to sliding motion that occurs between the chest wall and organs within the pleural sac (lungs, mediastinum, liver). In this paper we propose a methodology that (1) segments one of the images to be registered (the source or floating/moving image) into two distinct regions by fitting a statistical motion mask, and (2) registers the image with a modified B-spline registration algorithm that can account for sliding motion between the regions. This registration requires the segmentation of the regions in the source image domain as a signed distance map. Two underlying transformations allow the regions to deform independently, while a constraint term based on the transformed distance maps penalises gaps and overlaps between the regions. Although implemented in a B-spline algorithm, the required modifications are not specific to the transformation type and thus can be applied to parametric and non-parametric frameworks alike. The registration accuracy is evaluated using the landmark registration error on the basis of the publicly available DIR-Lab dataset. The overall average landmark error after registration is 1.21 mm and the average gap and overlap volumes are 26.4 cm³ and 34.5 cm³ respectively. The fitted statistical motion masks are compared to previously proposed motion masks and the corresponding mean Dice coefficient is 0.96.

Type: Proceedings paper
Title: Statistical Motion Mask and Sliding Registration
Event: 8th International Workshop, WBIR 2018
ISBN-13: 978-3-319-92258-4
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-92258-4_2
Publisher version: https://doi.org/10.1007/978-3-319-92258-4_2
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Sliding motion, B-Spline registration, Statistical shape model, Motion mask
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10051038
Downloads since deposit
80Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item