Graph Cuts-Based Registration Revisited: A Novel Approach for Lung Image Registration Using Supervoxels and Image-Guided Filtering
Szmul A, Papiez BW, Bates R, Hallack A, Schnabel JA, Grau V (2016)
Publication Type: Conference contribution
Publication year: 2016
Publisher: IEEE Computer Society
Pages Range: 592-599
Conference Proceedings Title: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Event location: Las Vegas, NV, USA
ISBN: 9781467388504
Abstract
This work revisits the concept of graph cuts as an efficient optimization technique in image registration. Previously, due to the computational burden involved, the use of graph cuts in this context has been mainly limited to 2D applications. Here we show how combining graph cuts with supervoxels, resulting in a sparse, yet meaningful graph-based image representation, can overcome previous limitations. Additionally, we show that a relaxed graph representation of the image allows for 'sliding' motion modeling and provides anatomically plausible estimation of the deformations. This is achieved by using image-guided filtering of the estimated sparse deformation field. We evaluate our method on a publicly available CT lung data set and show that our new approach compares very favourably with state-of-the-art in continuous and discrete image registration.
Involved external institutions
United Kingdom (GB)How to cite
APA:
Szmul, A., Papiez, B.W., Bates, R., Hallack, A., Schnabel, J.A., & Grau, V. (2016). Graph Cuts-Based Registration Revisited: A Novel Approach for Lung Image Registration Using Supervoxels and Image-Guided Filtering. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 592-599). Las Vegas, NV, USA: IEEE Computer Society.
MLA:
Szmul, Adam, et al. "Graph Cuts-Based Registration Revisited: A Novel Approach for Lung Image Registration Using Supervoxels and Image-Guided Filtering." Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016, Las Vegas, NV, USA IEEE Computer Society, 2016. 592-599.
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