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Updated: Feb 10, 2026

Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound
Published on: October 4, 2021
Enhancement of morphological and vascular features in OCT images using a modified Bayesian residual transform
Bingyao Tan1,2, Alexander Wong3,2, Kostadinka Bizheva1,3,4
1Department of Physics and Astronomy, University of Waterloo, Ontario, N2L 3G1, Canada.
Abstract:
A novel image processing algorithm based on a modified Bayesian residual transform (MBRT) was developed for the enhancement of morphological and vascular features in optical coherence tomography (OCT) and OCT angiography (OCTA) images. The MBRT algorithm decomposes the original OCT image into multiple residual images, where each image presents information at a unique scale. Scale selective residual adaptation is used subsequently to enhance morphological features of interest, such as blood vessels and tissue layers, and to suppress irrelevant image features such as noise and motion artefacts. The performance of the proposed MBRT algorithm was tested on a series of cross-sectional and enface OCT and OCTA images of retina and brain tissue that were acquired in-vivo. Results show that the MBRT reduces speckle noise and motion-related imaging artefacts locally, thus improving significantly the contrast and visibility of morphological features in the OCT and OCTA images.
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