1. Automatic 3D adaptive vessel segmentation based on linear relationship between intensity and complex-decorrelation in optical coherence tomography angiography

    Automatic 3D adaptive vessel segmentation based on linear relationship between intensity and complex-decorrelation in optical coherence tomography angiography

    Background: Vascular quantitative metrics have been widely used in the preclinical studies and clinical applications (e.g., the diagnosis and treatment of port wine stain, PWS), which require accurate vessel segmentation. An automatic 3D adaptive vessel segmentation is in need for a reproducible and objective quantification of the optical coherence tomography angiography (OCTA) image. Methods: Human skin imaging was performed with a lab-built optical coherence tomography (OCT) system. Rather than separately applying the conventional 2-step (intensity and binarization) thresholding in the decorrelation-contrast OCTA, we proposed a 3D adaptive threshold using the linear relationship between the local intensity and complex-decorrelation which ...

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