TopAwaRe: Topology-Aware Registration
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Deformable registration, or nonlinear alignment of images, is a fundamental preprocessing tool in medical imaging. State-of-the-art algorithms restrict to diffeomorphisms to regularize an otherwise ill-posed problem. In particular, such models assume that a one-to-one matching exists between any pair of images. In a range of real-life-applications, however, one image may contain objects that another does not. In such cases, the one-to-one assumption is routinely accepted as unavoidable, leading to inaccurate preprocessing and, thus, inaccuracies in the subsequent analysis. We present a novel, piecewise-diffeomorphic deformation framework which models topological changes as explicitly encoded discontinuities in the deformation fields. We thus preserve the regularization properties of diffeomorphic models while locally avoiding their erroneous one-to-one assumption. The entire model is GPU-implemented, and validated on intersubject 3D registration of T1-weighted brain MRI. Qualitative and quantitative results show our ability to improve performance in pathological cases containing topological inconsistencies.
Originalsprog | Engelsk |
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Titel | Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings |
Redaktører | Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou |
Antal sider | 9 |
Forlag | Springer VS |
Publikationsdato | 2019 |
Sider | 364-372 |
ISBN (Trykt) | 9783030322441 |
DOI | |
Status | Udgivet - 2019 |
Begivenhed | 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, Kina Varighed: 13 okt. 2019 → 17 okt. 2019 |
Konference
Konference | 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 |
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Land | Kina |
By | Shenzhen |
Periode | 13/10/2019 → 17/10/2019 |
Navn | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Vol/bind | 11765 LNCS |
ISSN | 0302-9743 |
ID: 237709464