Abstract
In diabetic patients, diabetic nephropathy is thought to be the leading end-stage renal disease. Proteinuria (excretion of excess protein in the urine) slowly improves diabetic nephropathy. A non-invasive imaging algorithm is desperately required to identify anomalies early in order to provide faster and improved care. As pre-processing and segmentation approaches the proposed algorithm uses enhancement. Equalization of histograms increases the global image contrast. Another version of histogram equalization computes multiple histograms, each corresponding to a separate section of the image and using them to redistribute and lighten the image value. CLAHE histogram equalization is an improvement of the previous method that works on specific regions of the image called titles rather than the whole image, and another technique, called dilation-based morphological reconstruction, is often used for preprocessing. Here Otsu thresholding is used as a post-processing tool that is used for automatic thresholding of images. This method is carried out on the R2018b and above version of MATLAB computing language.
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Sudha Rani, U., Subhas, C. (2021). Medical Imaging Analysis of Anomalies in Diabetic Nephropathy. In: Kumar, A., Mozar, S. (eds) ICCCE 2020. Lecture Notes in Electrical Engineering, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-15-7961-5_44
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DOI: https://doi.org/10.1007/978-981-15-7961-5_44
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