Certain investigations on vlsi implementation for classification of kidney images for health care applications

Abstract

In the past few decade medical imaging and associated systems are found to play vital role in developing an accurate computer assisted Medical Decision Support System for the clinical practitioners for better health care The development in the soft computing techniques further motivated the research to use them for developing more decision support systems It has been witnessed that the Ultrasound US image of kidney is preferred by most of the physicians for diagnosis of kidney It was also reported that identification of the kidney disease from the US image is considered to be the challenging task due to inherent limitations. With the development in the image processing tools the classification of US kidney has become accurate and preferred The proposed work was carried out in three phases in which the first phase was the selection of suitable filter for denoising the Kidney The performance of six filters namely Weighted Mean Filter WMF K Means Filter KMF Partitioned Filter PF Fuzzy C Means Filter FCMF Shock Filter SF and Adaptive Shock Filter ASF were analysed The analysis was carried out based on the performance of the parameters namely Mean Square Error Peak Signal to Noise Ratio Contrast to Noise Ratio Image Quality Index and Mean Absolute Error The Adaptive Shock filter outperforms other filter to denoise the image without affecting the edges newline