Computational Analysis and Deep Learning for Medical Care

8Disease Detection Platform Using Image Processing Through OpenCV

Neetu Faujdar^1* and Aparna Sinha²

¹Department of Computer Science, GLA University, Mathura, India

²Department of Computer Science, Amity University, Noida, India

Abstract

Presently, methods accessible for Glaucoma detection revolve around the usage of devices such as Digital Single-Lens Reflex (DSLR) camera, and these are extremely pricey. Same are the instances for eye and skin cancer. Apart from the fact that these are costly methods, they are also inaccessible to a majority of people. Thus, the main objective behind this chapter is to design useful and effective algorithms that, in turn, shall prove to be robust and cost-effective too. We strive to enroot algorithms that are capable of running on the required devices so that the disease detection platform can be widened, thereafter enabling us to take necessary actions.

Taking into consideration cataract, the screening can be efficiently done using the proposed algorithm that focuses on analysis based on texture features like uniformity, standard deviation, and intensity.

Similarly, retinoblastoma cancer can be detected via the automatized detection technique for immature cells in the retina. The idea is to encapsulate an image processing algorithm that, in turn, would be helpful for detection of white radius of retina with the help of image filtering, canny edge detection, and thresholding. These techniques of image processing have simplified the diagnosis ...