Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
In diabetes retinopathy, identification of Micro aneurysms is an important phase for treatment of diabetic patients. The clustering technique which we are going to present identifies micro aneurysms from optic disk in the retinal fundus pictures. Constrained Spectral Clustering (CSC) has shown great deal with images to identify MA in medical retinal images with increasing accuracy in image segmentation. CSC performs by integrating sparse based coding to construct efficient frames based on clustering in image segmentation to identify MAs in retinal images for better image segmentation in pixel calculation in large image data sets present in application processing. So in this study, we extend CSC with Fuzzy C-Means (FCM) Clustering. FCM is used to cluster the data in which the dataset is grouped into n clusters. Every data point of the dataset belongs to every cluster to a certain degree. In FCM, we perform efficient clustering with spatial pixel evaluation in retinal images with diabetic retinal images to divide spectral coding in medical decision analysis with preferable operations.
How to cite this article:
Kalla Sai Sreenivas and G. Pradeepini. Detection of the Presence of Micro Aneurysms in Retinal Images using FCM.
DOI: https://doi.org/10.36478/ajit.2020.181.185
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2020.181.185