Detection and comparison of Diabetic Glaucoma using K-means Algorithm and Thresholding Algorithm

Autor: D.J. Rani, F. Naz
Rok vydání: 2023
Předmět:
Zdroj: CARDIOMETRY. :858-864
DOI: 10.18137/cardiometry.2022.25.858864
Popis: Aim: The aim of this research work is for the Innovative Diabetic Glaucoma Detection using modern algorithms and comparing the peak signal to noise ratio (PSNR) between K-means Algorithm and Thresholding Algorithm. Materials and Methods: The sample images were taken from Kaggle’s website. Samples were considered as (N=24) for K-Means Algorithm and (N=24) for Thresholding Algorithm in accordance with total sample size calculated using clinicalc.com by keeping alpha error threshold value 0.05, enrollment rati as 0.1, 95% confidence interval, G power as 80%. The PSNR was calculated by using the MATLAB Programming with standard datasets. Results: Comparison of PSNR is done by independent sample t-test using SPSS software. There is a statistical significant difference between the K-Means Algorithm and Thresholding Algorithm with p= 0.001, p
Databáze: OpenAIRE