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.
Highlights
Optical Coherence Tomography (OCT) is a non-invasive, high-resolution medical imaging modality that can resolve morphological features in biological tissue as small as individual cells, at imaging depths in the order of 1mm below the tissue surface [1]
Morphological features of interest in OCT and OCT angiography (OCTA) are masked or compromised by speckle noise, motion artefacts and shadow artefacts generated by superficial blood vessels over deeper tissue layers due to scattering and absorption of light by the blood cells
We describe the modified Bayesian residual transform (MBRT) approach in detail and present enhanced images that were acquired in-vivo from human and rats with different customized OCT systems and a commercial system, and with different spatial resolutions, image acquisition rates and noise levels
Summary
Optical Coherence Tomography (OCT) is a non-invasive, high-resolution medical imaging modality that can resolve morphological features in biological tissue as small as individual cells, at imaging depths in the order of 1mm below the tissue surface [1]. An extension of OCT, named OCT angiography (OCTA), is able to image non-invasively the vasculature of biological tissue by removing the imaging data corresponding to static tissue and emphasizing the regions that exhibit tissue motion [3]. Quantitative analysis of OCT and OCTA images, such as segmentation and thickness measurement of tissue layers, pattern analysis to identify regions of tissue where the morphology has been affected by a pathology from regions of healthy tissue, segmentation and sizing of blood and lymph vasculature, etc., has a significant clinical value as it can assist physicians with the diagnosis and treatment of various diseases. Morphological features of interest in OCT and OCTA are masked or compromised by speckle noise, motion artefacts and shadow artefacts generated by superficial blood vessels over deeper tissue layers due to scattering and absorption of light by the blood cells
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