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Automated Cone and Vessel Analysis in Adaptive Optics Like Retinal Images for Clinical Diagnostics Support

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
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Autor(en): Hertlein, Anna-Sophia ; Wesarg, Stefan ; Schmidt, Jessica ; Boche, Benjamin ; Pfeiffer, Norbert ; Matlach, Juliane
Art des Eintrags: Bibliographie
Titel: Automated Cone and Vessel Analysis in Adaptive Optics Like Retinal Images for Clinical Diagnostics Support
Sprache: Englisch
Publikationsjahr: 10 Januar 2023
Verlag: Springer
Buchtitel: Clinical Image-Based Procedures
Reihe: Lecture Notes in Computer Science
Band einer Reihe: 13746
Veranstaltungstitel: 11th International Workshop on Clinical Image-based Procedures
Veranstaltungsort: Singapore
Veranstaltungsdatum: 18.09.2022
DOI: 10.1007/978-3-031-23179-7_9
Kurzbeschreibung (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.

Freie Schlagworte: Vessel segmentation, High magnification module (HMM), Adaptive optics (AO)
Zusätzliche Informationen:

In conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022)

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 06 Mär 2023 10:38
Letzte Änderung: 10 Aug 2023 13:11
PPN: 510502008
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