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Comparative Analysis of Segmentation techniques for Progressive Evaluation and Risk Identification of Diabetic Foot Ulcers

Diabetes Mellitus is a chronic disease that affects human body due to damaged pancreas producing insufficient amount of insulin. Diabetes is a lifelong disease that usually damage kidneys, eyes, heart and also nerve damages in the feet. Diabetes have major cause of mortality and disability from foot ulcers if left untreated. Nowadays there are different imaging techniques such as CT, MRI and PET used in diagnosis of human body. Among which Infrared thermography is best suited for interpreting the pathophysiologic information on metabolic, thermal and vascular conditions of human body. This method of scanning is noninvasive, non-destructive and do not require any physical contact for the scanned object. Studies and clinical observations proves that IR thermography detects the diseases in early phase and provides the information for suitable therapeutic treatment. It is usual fact that accuracy of diagnosis in IR imaging depends on segmentation of Region of Interest (ROI). Image segmentation algorithms automatically detect the region of interest and optimize the result for accurate extraction of measurements when compared to other methods. The present work defines some of the segmentation algorithms with various results in optimizing ROI’s.