Conference paper · Book chapter
Automated Quantification of Retinal Microvasculature from OCT Angiography using Dictionary-Based Vessel Segmentation
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
University of Copenhagen3
Statistics and Data Analysis, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Investigations in how the retinal microvasculature correlates with ophthalmological conditions necessitate a method for measuring the microvasculature. Optical coherence tomography angiography (OCTA) depicts the superficial and the deep layer of the retina, but quantification of the microvascular network is still needed.
Here, we propose an automatic quantitative analysis of the retinal microvasculature. We use a dictionary-based segmentation to detect larger vessels and capillaries in the retina and we extract features such as densities and vessel radius. The method is validated on repeated OCTA scans from healthy subjects, and we observe high intraclass correlation coecients and high agreement in a Bland-Altman analysis.
The quantification method is also applied to pre- and postoperative scans of cataract patients. Here, we observe a higher variation between the measurements, which can be explained by the greater variation in scan quality. Statistical tests of both the healthy subjects and cataract patients show that our method is able to di↵erentiate subjects based on the extracted microvascular features.
Language: | English |
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Publisher: | Springer |
Year: | 2019 |
Pages: | 257-269 |
Proceedings: | 23rd Conference on Medical Image Understanding and Analysis |
Series: | Communications in Computer and Information Science |
ISBN: | 3030393429 , 3030393437 , 9783030393427 and 9783030393434 |
ISSN: | 18650929 and 18650937 |
Types: | Conference paper and Book chapter |
DOI: | 10.1007/978-3-030-39343-4_22 |
ORCIDs: | Dahl, Anders Bjorholm and Dahl, Vedrana Andersen |