Open Access


An Ophthalmic Evaluation of Central Serous Chorioretinopathy

L. K. Shoba1,*, P. Mohan Kumar2
1 Department of Information Technology, Jeppiaar Engineering College, Chennai, 600119, India
2 Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, 641008, India
* Corresponding Author: L. K. Shoba. Email:

Computer Systems Science and Engineering 2023, 44(1), 613-628.

Received 18 October 2021; Accepted 05 January 2022; Issue published 01 June 2022


Nowadays in the medical field, imaging techniques such as Optical Coherence Tomography (OCT) are mainly used to identify retinal diseases. In this paper, the Central Serous Chorio Retinopathy (CSCR) image is analyzed for various stages and then compares the difference between CSCR before as well as after treatment using different application methods. The first approach, which was focused on image quality, improves medical image accuracy. An enhancement algorithm was implemented to improve the OCT image contrast and denoise purpose called Boosted Anisotropic Diffusion with an Unsharp Masking Filter (BADWUMF). The classifier used here is to figure out whether the OCT image is a CSCR case or not. 150 images are checked for this research work (75 abnormal from Optical Coherence Tomography Image Retinal Database, in-house clinical database, and 75 normal images). This article explicitly decides that the approaches suggested aid the ophthalmologist with the precise retinal analysis and hence the risk factors to be minimized. The total precision is 90 percent obtained from the Two Class Support Vector Machine (TCSVM) classifier and 93.3 percent is obtained from Shallow Neural Network with the Powell-Beale (SNNWPB) classifier using the MATLAB 2019a program.


OCT; CSCR; macula; segmentation; boosted anisotropic diffusion with unsharp masking filter; two class support vector machine classifier and shallow neural network with powell-beale classifier

Cite This Article

L. K. Shoba and P. Mohan Kumar, "An ophthalmic evaluation of central serous chorioretinopathy," Computer Systems Science and Engineering, vol. 44, no.1, pp. 613–628, 2023.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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