Abstract
Optical coherence tomography angiography (OCTA) is a popular medical imaging technology that can quickly establish a three-dimensional model of the fundus without dye injection. However the number of images in a model is quite large, so finding the lesions through image processing technology can greatly reduce the time required for the judgment of the condition. This paper proposes a method for finding choroidal neovascularization (CNV) in OCTA images. Among the several characteristics of CNV, the larger turning angle of blood vessels is a relatively clear feature, so we will use this property to find out whether there is CNV in an OCTA image. We will transform the color space to CIELAB space, and extract the L-channel prior to preceding to the next step. We will then use some image segmentation methods to find the clearer vessel region. Finally, we will detect the CNV through certain morphology methods. The experimental result shows that our proposed method can effectively find the CNV in the OCTA image, meaning that we can make automated judgments through this method in the future and reduce the time necessary for human judgment.
Highlights
Age-related macular degeneration (AMD) is the leading cause of vision impairment and severe visual loss amongst older individuals in developed countries [1]
We use some image segmentation methods to find the clearer blood vessels, and create the difference in its appearance to allow the computer to identify the choroidal neovascularization (CNV). We hope this method could be applied in the medical field in the future to reduce both the burden on doctors and the time required for disease diagnosis
Several optical coherence tomography (OCTA) images were used in the experiment to test whether the scheme we proposed could locate the choroidal neovascularization (CNV)
Summary
Age-related macular degeneration (AMD) is the leading cause of vision impairment and severe visual loss amongst older individuals in developed countries [1]. 196 million in 2020, increasing to 288 million in 2040 [2] It is a significant public health problem. Detection of CNV in patients with exudative AMD is critical for early treatment and the prevention of vision loss [4]. Both fluorescein angiography (FA) and indocyanine green angiography (ICGA) are chief diagnostic methods for CNV detection [5]. Both modalities are considered invasive and time consuming, requiring intravenous dye injections, while posing a potential risk for anaphylaxis [6]
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