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

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.

OriginalspracheEnglisch
Aufsatznummer046005
ZeitschriftJournal of Biomedical Optics
Jahrgang24
Ausgabenummer04
Seiten (von - bis)1-11
Seitenumfang11
ISSN1083-3668
DOIs
PublikationsstatusVeröffentlicht - 30.04.2019

Strategische Forschungsbereiche und Zentren

  • Forschungsschwerpunkt: Biomedizintechnik

Fingerprint

Untersuchen Sie die Forschungsthemen von „Optimization-based vessel segmentation pipeline for robust quantification of capillary networks in skin with optical coherence tomography angiography“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren