Enhancement of morphological and vascular features in OCT images using a modified Bayesian residual transform

Biomedical Optics Express
Bingyao TanKostadinka Bizheva

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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Mar 21, 2017·Investigative Ophthalmology & Visual Science·Bingyao TanKostadinka K Bizheva
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Citations

Oct 3, 2020·Translational Biophotonics·Yan LiZhongping Chen
Oct 6, 2020·Biomedical Optics Express·Min GaoYali Jia
Dec 12, 2018·Clinical & Experimental Optometry : Journal of the Australian Optometrical Association·Jacqueline ChuaLeopold Schmetterer
Dec 5, 2019·Biomedical Optics Express·Bernhard BaumannChristoph K Hitzenberger
Mar 27, 2021·Progress in Retinal and Eye Research·Tristan T HormelYali Jia
Jul 16, 2021·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Lei ChenZhenkun Lei
Aug 31, 2021·Biomedical Optics Express·Bingyao TanLeopold Schmetterer

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