Name
Title | ||
|---|---|---|
Mutual Information Neural Estimation for Unsupervised Multi-Modal Registration of Brain Images. |
Abstract | ||
|---|---|---|
Many applications in image-guided surgery and therapy require fast and reliable non-linear, multi-modal image registration. Recently proposed unsupervised deep learning-based registration methods have demonstrated superior per-formance compared to iterative methods in just a fraction of the time. Most of the learning-based methods have focused on mono-modal image registration. The extension to multi-modal registration depends on the use of an appropriate similarity function, such as the mutual information (MI). We propose guiding the training of a deep learning-based registration method with MI estimation between an image-pair in an end-to-end trainable network. Our results show that a small, 2-layer network produces competitive results in both mono- and multi-modal registration, with sub-second run-times. Comparisons to both iterative and deep learning-based methods show that our MI-based method produces topologically and qualitatively superior results with an extremely low rate of non-diffeomorphic transformations. Real-time clinical application will benefit from a better visual matching of anatomical structures and less registration failures/outliers. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/EMBC48229.2022.9871220 | Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
DocType | Volume | ISSN |
Conference | 2022 | 2694-0604 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gerard Snaauw | 1 | 0 | 0.68 |
| Michele Sasdelli | 2 | 0 | 1.01 |
| Gabriel Maicas | 3 | 0 | 0.34 |
| Stephan Lau | 4 | 3 | 0.76 |
| Johan Verjans | 5 | 0 | 0.68 |
| Mark Jenkinson | 6 | 142 | 5.82 |
| Gustavo Carneiro | 7 | 1153 | 69.37 |