Hertlein, Anna-Sophia ; Wesarg, Stefan ; Schmidt, Jessica ; Boche, Benjamin ; Pfeiffer, Norbert ; Matlach, Juliane (2023)
Automated Cone and Vessel Analysis in Adaptive Optics Like Retinal Images for Clinical Diagnostics Support.
11th International Workshop on Clinical Image-based Procedures. Singapore (18.09.2022)
doi: 10.1007/978-3-031-23179-7_9
Conference or Workshop Item, Bibliographie
Abstract
Today, modern non-invasive Adaptive Optics (AO) imaging enables visualization of cone photoreceptors and vessels on a cellular level. High Magnification Module (HMM) images strongly resemble AO images and can be acquired fast and cost-effectly in clinical routine. Manual examination of those images, however, is tedious and time-consuming. Therefore, methods are needed to automatically analyse HMM images to facilitate the work of ophthalmologists. In this work an automatic cone detection method is presented that robustly detects cones in these images of both healthy and glaucoma patients. In addition, a vessel segmentation algorithm is provided to mask vessels during cone detection and additionally provide the ophthalmologist with vessel diameters that aid in monitoring ocular and cardiovascular diseases. The results on the given data are comparable to the performance of a trained expert and the methods are already being used in clinical practice.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2023 |
| Creators: | Hertlein, Anna-Sophia ; Wesarg, Stefan ; Schmidt, Jessica ; Boche, Benjamin ; Pfeiffer, Norbert ; Matlach, Juliane |
| Type of entry: | Bibliographie |
| Title: | Automated Cone and Vessel Analysis in Adaptive Optics Like Retinal Images for Clinical Diagnostics Support |
| Language: | English |
| Date: | 10 January 2023 |
| Publisher: | Springer |
| Book Title: | Clinical Image-Based Procedures |
| Series: | Lecture Notes in Computer Science |
| Series Volume: | 13746 |
| Event Title: | 11th International Workshop on Clinical Image-based Procedures |
| Event Location: | Singapore |
| Event Dates: | 18.09.2022 |
| DOI: | 10.1007/978-3-031-23179-7_9 |
| Abstract: | Today, modern non-invasive Adaptive Optics (AO) imaging enables visualization of cone photoreceptors and vessels on a cellular level. High Magnification Module (HMM) images strongly resemble AO images and can be acquired fast and cost-effectly in clinical routine. Manual examination of those images, however, is tedious and time-consuming. Therefore, methods are needed to automatically analyse HMM images to facilitate the work of ophthalmologists. In this work an automatic cone detection method is presented that robustly detects cones in these images of both healthy and glaucoma patients. In addition, a vessel segmentation algorithm is provided to mask vessels during cone detection and additionally provide the ophthalmologist with vessel diameters that aid in monitoring ocular and cardiovascular diseases. The results on the given data are comparable to the performance of a trained expert and the methods are already being used in clinical practice. |
| Uncontrolled Keywords: | Vessel segmentation, High magnification module (HMM), Adaptive optics (AO) |
| Additional Information: | In conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022) |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Date Deposited: | 06 Mar 2023 10:38 |
| Last Modified: | 10 Aug 2023 13:11 |
| PPN: | 510502008 |
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| Suche nach Titel in: | TUfind oder in Google |
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