TopAwaRe: Topology-Aware Registration
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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.
Original language | English |
---|---|
Title of host publication | Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings |
Editors | Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou |
Number of pages | 9 |
Publisher | Springer VS |
Publication date | 2019 |
Pages | 364-372 |
ISBN (Print) | 9783030322441 |
DOIs | |
Publication status | Published - 2019 |
Event | 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China Duration: 13 Oct 2019 → 17 Oct 2019 |
Conference
Conference | 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 |
---|---|
Land | China |
By | Shenzhen |
Periode | 13/10/2019 → 17/10/2019 |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|
Volume | 11765 LNCS |
ISSN | 0302-9743 |
- Diffeomorphisms, Image registration, Topology-Aware
Research areas
ID: 237709464