Sindel A, Hohberger B, Maier A, Christlein V (2022)
Publication Language: English
Publication Status: Accepted
Publication Type: Conference contribution
Future Publication Type: Conference contribution
Publication year: 2022
Publisher: Springer, Cham
Series: MICCAI 2022. Lecture Notes in Computer Science
Book Volume: vol 13436
Pages Range: 108–118
Conference Proceedings Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022
Event location: Singapore
ISBN: 978-3-031-16446-0
DOI: 10.1007/978-3-031-16446-0_11
Open Access Link: https://arxiv.org/pdf/2207.10506.pdf
In ophthalmological imaging, multiple imaging systems, such as color fundus, infrared, fluorescein angiography, optical coherence tomography (OCT) or OCT angiography, are often involved to make a diagnosis of retinal disease. Multi-modal retinal registration techniques can assist ophthalmologists by providing a pixel-based comparison of aligned vessel structures in images from different modalities or acquisition times. To this end, we propose an end-to-end trainable deep learning method for multi-modal retinal image registration. Our method extracts convolutional features from the vessel structure for keypoint detection and description and uses a graph neural network for feature matching. The keypoint detection and description network and graph neural network are jointly trained in a self-supervised manner using synthetic multi-modal image pairs and are guided by synthetically sampled ground truth homographies. Our method demonstrates higher registration accuracy as competing methods for our synthetic retinal dataset and generalizes well for our real macula dataset and a public fundus dataset.
APA:
Sindel, A., Hohberger, B., Maier, A., & Christlein, V. (2022). Multi-modal Retinal Image Registration Using a Keypoint-Based Vessel Structure Aligning Network. In Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 (pp. 108–118). Singapore: Springer, Cham.
MLA:
Sindel, Aline, et al. "Multi-modal Retinal Image Registration Using a Keypoint-Based Vessel Structure Aligning Network." Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022, Singapore Ed. Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S., Springer, Cham, 2022. 108–118.
BibTeX: Download