The week's pick
Reseach Article
Novel Hybrid Bio-medical Image Processing Algorithms for the Detection of Glaucoma Disease in Human Eyes using AI-ML and Real Time Embedded System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 40 |
| Year of Publication: 2022 |
| Authors: Tian Jipeng, Hou Lingmei, G. Hemantha Kumar |
10.5120/ijca2022922515
|
Tian Jipeng, Hou Lingmei, G. Hemantha Kumar . Novel Hybrid Bio-medical Image Processing Algorithms for the Detection of Glaucoma Disease in Human Eyes using AI-ML and Real Time Embedded System. International Journal of Computer Applications. 184, 40 ( Dec 2022), 37-40. DOI=10.5120/ijca2022922515
Abstract
Glaucoma is the second largest disease in the world after cancer (different types) & is a silent thief/killer of sight which is characterized by the increase in the intraocular pressure with slow vision loss leading to permanent blindness. Although the disease is incurable, but its symptoms can be minimized-therefore early detection of the disease is essential. It is a very expensive process to detect the disease using the modern tools as a result of which we are developing some sort of novel methodologies for the detection process (using off line methods) such that it is affordable by all the sections of the society, also it can be detected at the early stage and prevention can be taken after follow ups. The Artificial Intelligence (AI) & Machine Learning (ML) concepts are going to be used in the detection process by developing hybrid algorithms. Various types of glaucoma exist, for example, primary, secondary & the higher order ones. Hybrid algos could be developed and used for detection purposes with more efficiency compared to the works done till date. The software tools such as MATLAB, Xilinx, Modalism, LabVIEW, Kiel, HDL, could be planned to be used for the simulation purposes for the disease detection process. The work done in the simulation stage could be evaluated or validated using a real time embedded system or by the usage of some interfacing hardware of a suitable type, which may be a DSP based TMS board or a FPGA kit or a Micro-controller Kit or a Raspberry Pi or it can be any new interfacing device.
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