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Segmentation and Analysis of Renal Biopsies and Histological Images of Diabetic Nephropathy Using Otsu’s Method.
Yogini B.Patil and Seema Kawathekar

Published in: Journal for Advance Research in Applied Sciences
Volume- 4, Issue-4, pp.18-22, Sep 2017
DPI :-> 16.10089.JARAS.2017.V4I4.1822.1937



Abstract
Diabetic nephropathy is a significant cause of chronic kidney disease and end-stage renal failure globally. Much research has been conducted in both basic science and clinical therapeutics, which has enhanced understanding of the path physiology of diabetic nephropathy and expanded the potential therapies available. The computational technology enhanced towards medical research, substantial research work has been done towards analysis of Diabetic nephropathy. It is a challenging task as 100% detection of Nephropathy disease with the regular pathological procedure is not possible [1]. We propose a solution to the problem of segmentation of the renal Biopsies images for the analysis. This research work examined the analysis of diabetic nephropathy in the context of the Otus image segmentation approach. The quality of proposed image segmentation is evaluated using SNR and PSNR statistical measure. SNR is 90%. The PSNR based quality of segmentation is 100%. The rate of recognition can be further improved by increasing the size of the database and by considering the better statistical measure

Key-Words / Index Term
Diabetic Nephropathy, Chan-base model, PSNR.

How to cite this article
Yogini B.Patil and Seema Kawathekar , “Segmentation and Analysis of Renal Biopsies and Histological Images of Diabetic Nephropathy Using Otsu’s Method.”, Journal for Advance Research in Applied Sciences, 4, Issue-4, pp.18-22, Sep 2017. DPI:16.10089.JARAS.V4.I4.1937