Morphological Watershed Approach for the Analysis of Diabetic Nephropathy

Abstract

The main cause of progressive kidney failure and a significant cause of coronary mortality is diabetic nephropathy. The application of Watershed segmentation and Gradient magnitude has produced encouraging results among the image processing methods for detecting anomalies. The suggested algorithms using optimization as pre-processing and as post-processing approaches for segmentation. Clahe histogram equalization is an improvement of the previous approach that operates on specific parts of the image named titles rather than the entire image, and even another tool named dilation-based morphological reconstruction is used for pre-processing. Otsu Thresholding is used as a post-processing tool and is used to do automate image Thresholding. The Median filter is also used to eliminate noise from the signal and often retains the image edges when eliminating noise. The Segmentation of the Morphological Wetlands will accurately distinguish items on the foreground and context. The picture collection for this phase is from CT photographs of patients with diabetic nephropathy, as well as from Diabetic research institutes.