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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 10 Issue: 08 | Aug 2023

p-ISSN: 2395-0072

www.irjet.net

SVM based CSR disease detection for OCT and Fundus Imaging [1]Arpitha C N,

[3] Archana P,

[1] Asst. Professor, CS&E Department,

[3] Asst. Professor, CS&E Department,

[1] Adichunchanagiri Institute of Technology

[3] Adichunchanagiri Institute of Technology

[2] Revani Naik,

[4] Kavya.T.M

[1] Chikamagaluru, India

[3] Chikamagaluru, India

[2] M.Tech. Scholar, CS&E Department,

[4] Asst. Professor, CS&E Department,

[2] Adichunchanagiri Institute of Technology

[4] Adichunchanagiri Institute of Technology

[2] Chikamagaluru, India

[4] Chikamagaluru, India

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Abstract — CSR is a retinal disease that affects vision

1.1 Structure of the Eye

and causes blindness. The CSR is brought on by an accumulation of watery fluid behind the retina. The early detection and treatment of CSR disease enables the avoidance and cure of eye damage. Retinal diseases include glaucoma, Drusen, and diabetic retinopathy (DR), as well as Central Serous Retinopathy (CSR), Choroidal Neovascularization (CNV), Age-Related Macular Degeneration (AMD), Diabetic Macula Edema (DME), and Age-Related Macular Atrophy (ARMA). Several cutting-edge methods and research assist the automatic identification of CSR. Two imaging techniques were employed to identify CSR disease. The two imaging or scanning (dataset) methods used are optical coherence tomography (OCT) angiography and fundus imaging. The novel based technology used in this work provides automatic CSR detection. A Support Vector Machine (SVM) is used to categorize and identify CSR disease. The findings after implementation are examined and presented.

The regions of the human eye that are most easily identified are the sclera, cornea, iris, and pupil. The internal surface is made up of the retina, macular, fovea, optic disc, and posterior pole, as depicted in Fig. 1. When we gaze at something, light enters our eyes through the cornea, where it partially concentrates the image before reaching the pupil and lens. The image is further strengthened by the lens. After passing through the vitreous, the picture is focused on the macula, a portion of the central retina [12]. For tasks like reading, writing, and colour discrimination, humans can perceive fine detail thanks to this specialized area of the retina. The second half of the retina, known as the peripheral retina, regulates side vision. The retina, a layer of tissue in the eye, converts light that enters into a neural signal that is then sent to the brain for additional processing [13]. As a result, the retina serves as a brain extension. A web of blood arteries supplies the retina with blood. For instance, diabetes has the ability to harm the retina's blood vessels and impair its functionality.

Keywords - Support Vector Machine (SVM), Central Serous Retinopathy (CSR), OCT imaging and Fundus imaging. 1. INTRODUCTION Retina is a thin layer which is made up of sensitive tissues that is located beneath the eyeball, near to the optic nerve. It takes the concentrated light signals which comes from eye lens, transforms to neural impulses, and then transmits those signals to the brain, so that brain can interpret the images. The anatomy of the retina and an overview of the most prevalent retinal diseases, including glaucoma, cardiovascular disease, AMD, CNV, and CSR, DR, and DME, are provided in this section. The following section covers the imaging techniques used for classifying and detect retinal diseases. This study is interested in CSR disease.

Impact Factor value: 8.226

Fig. 1: schematic of human eye Using imaging techniques including fundus photography, auto-fluorescence (AF), optical coherence tomography (OCT) and angiography, one may diagnose retinal retina and identify CSR diseases. In more recent Deep Learning (DL) studies, each patient are potential source of priceless diagnostic information that would be utilized to train current Machine Learning (ML) models to obtain improved treatment and diagnosis. The creation of marks and changes in the layers are the disease features on

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