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Automatic Detection of Blood Vessels in Optical Coherence Tomography Scans

: Hofmann, Julia; Böge, Melanie; Gladysz, Szymon; Jutzi, Boris

Postprint urn:nbn:de:0011-n-5411628 (284 KByte PDF)
MD5 Fingerprint: 488073150c5cb0617dc42b293b5b2654
The original publication is available at
Created on: 20.03.2020

Handels, H.:
Bildverarbeitung für die Medizin 2019 : Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 17. bis 19. März 2019 in Lübeck
Wiesbaden: Springer Fachmedien, 2019 (Informatik aktuell)
ISBN: 978-3-658-25325-7 (Print)
ISBN: 978-3-658-25326-4 (Online)
ISBN: 3-658-25325-8
Workshop Bildverarbeitung für die Medizin (BVM) <2019, Lübeck>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

The aim of this research is to develop a new automated blood vessel (BV) detection algorithm for optical coherence tomography (OCT) scans and corresponding fundus images. The algorithm provides a robust method to detect BV shadows (BVSs) using Radon transformation and other supporting image processing methods. The position of the BVSs is determined in OCT scans and the BV thickness is measured in the fundus images. Additionally, the correlation between BVS thickness and retinal nerve fiber layer (RNFL) thickness is determined. This correlation is of great interest since glaucoma, for example, can be identified by a loss of RNFL thickness.