Sindel A, Hohberger B, Fassihi Dehcordi S, Mardin CY, Lämmer R, Maier A, Christlein V (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: Springer
Series: Informatik aktuell
City/Town: Wiesbaden
Pages Range: 57–62
Conference Proceedings Title: Bildverarbeitung für die Medizin 2022
Event location: Heidelberg
ISBN: 978-3-658-36932-3
URI: https://arxiv.org/pdf/2201.02242.pdf
DOI: 10.1007/978-3-658-36932-3_12
Ophthalmological imaging utilizes different imaging systems, such as color fundus, infrared, fluorescein angiography, optical coherence tomography (OCT) or OCT angiography. Multiple images with different modalities or acquisition times are often analyzed for the diagnosis of retinal diseases. Automatically aligning the vessel structures in the images by means of multi-modal registration can support the ophthalmologists in their work. Our method uses a convolutional neural network to extract features of the vessel structure in multi-modal retinal images. We jointly train a keypoint detection and description network on small patches using a classification and a cross-modal descriptor loss function and apply the network to the full image size in the test phase. Our method demonstrates the best registration performance on our and a public multi-modal dataset in comparison to competing methods.
APA:
Sindel, A., Hohberger, B., Fassihi Dehcordi, S., Mardin, C.Y., Lämmer, R., Maier, A., & Christlein, V. (2022). A Keypoint Detection and Description Network Based on the Vessel Structure for Multi-modal Retinal Image Registration. In Maier-Hein, K., Deserno, T.M., Handels, H., Maier, A., Palm, C., Tolxdorff, T. (Eds.), Bildverarbeitung für die Medizin 2022 (pp. 57–62). Heidelberg: Wiesbaden: Springer.
MLA:
Sindel, Aline, et al. "A Keypoint Detection and Description Network Based on the Vessel Structure for Multi-modal Retinal Image Registration." Proceedings of the Bildverarbeitung für die Medizin 2022, Heidelberg Ed. Maier-Hein, K., Deserno, T.M., Handels, H., Maier, A., Palm, C., Tolxdorff, T., Wiesbaden: Springer, 2022. 57–62.
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