Optimization-based vessel segmentation pipeline for robust quantification of capillary networks in skin with optical coherence tomography angiography

Malte Casper; Hinnerk Schulz-Hildebrandt; Michael Evers; Reginald Birngruber; Dieter Manstein; Gereon Hüttmann

doi:10.1117/1.JBO.24.4.046005

30 April 2019 Optimization-based vessel segmentation pipeline for robust quantification of capillary networks in skin with optical coherence tomography angiography

Malte Casper, Hinnerk Schulz-Hildebrandt, Michael Evers, Reginald Birngruber, Dieter Manstein, Gereon Hüttmann

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Journal of Biomedical Optics, Vol. 24, Issue 4, 046005 (April 2019). https://doi.org/10.1117/1.JBO.24.4.046005

Abstract

Optical coherence tomography angiography (OCTA) provides in-vivo images of microvascular perfusion in high resolution. For its application to basic and clinical research, an automatic and robust quantification of the capillary architecture is mandatory. Only this makes it possible to reliably analyze large amounts of image data, to establish biomarkers, and to monitor disease developments. However, due to its optical properties, OCTA images of skin often suffer from a poor signal-to-noise ratio and contain imaging artifacts. Previous work on automatic vessel segmentation in OCTA mostly focuses on retinal and cerebral vasculature. Its applicability to skin and, furthermore, its robustness against imaging artifacts had not been systematically evaluated. We propose a segmentation method that improves the quality of vascular quantification in OCTA images even if corrupted by imaging artifacts. Both the combination of image processing methods and the choice of their parameters are systematically optimized to match the manual labeling of an expert for OCTA images of skin. The efficacy of this optimization-based vessel segmentation is further demonstrated on sample images as well as by a reduced error of derived quantitative vascular network characteristics.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Malte Casper, Hinnerk Schulz-Hildebrandt, Michael Evers, Reginald Birngruber, Dieter Manstein, and Gereon Hüttmann "Optimization-based vessel segmentation pipeline for robust quantification of capillary networks in skin with optical coherence tomography angiography," Journal of Biomedical Optics 24(4), 046005 (30 April 2019). https://doi.org/10.1117/1.JBO.24.4.046005

Received: 9 December 2018; Accepted: 1 April 2019; Published: 30 April 2019

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