At present there is an increased interest in Therapeutic
image processing in most fields of engineering. Imaging modality provides
detailed information about anatomy. It is also helpful in the finding of the
disease and its progressive treatment. The Prime signs of Diabetic Retinopathy(DR) are Exudates which leads to severe vision loss in chronic condition.
Exudates are the remnant of exuded blood and protein based particles from the
damaged blood vessels of retina. Laser healing requires accurate location of
exudates for faithful removal through Laser burns. Segmentation of fundoscope
image will help the ophthalmologist in diagnosis, classification and to
determine the severity. Multiple methods are designed and developed for Medical
Image segmentation based on thresholding, Region Growing, Markov Random Model,
Clustering, Deformable Model, Classifier, Neural Networks, Expectation
Maximization and Support vector machines etc. Out of these the fuzzy clustering
methods are less complex and are robust in operation. This paper aims in
performance evaluation of Fuzzy C means clustering (FCM) algorithm, Kernel
induced FCM (KFCM) and Spatial FCM (SFCM) algorithms are done.
Diabetes is a chronic condition which requires lifelong
therapeutic care and edification of self-management by the patient to put offinitial complications and to lessen the threat of continuing problems. Beyond
glycemic control, its care is quite complex as it poses the root cause of many
issues.
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