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Sweety Maniar
Department of Computer/IT Engineering, Gujarat Technological University, Gujarat
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Classification of Content based Medical Image Retrieval Using Texture and Shape feature with Neural Network Sweety Maniar; Jagdish S. Shah
International Journal of Advances in Applied Sciences Vol 6, No 4: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.707 KB) | DOI: 10.11591/ijaas.v6.i4.pp368-374

Abstract

Medical image classification and retrieval systems have been finding extensive use in the areas of image classification according to imaging modalities, body part and diseases. One of the major challenges in the medical classification is the large size images leading to a large number of extracted features which is a burden for the classification algorithm and the resources. In this paper, a novel approach for automatic classification of fundus images is proposed. The method uses image and data pre-processing techniques to improve the performance of machine learning classifiers. Some predominant image mining algorithms such as Classification, Regression Tree (CART), Neural Network, Naive Bayes (NB), Decision Tree (DT) K-Nearest Neighbor. The performance of MCBIR systems using texture and shape features efficient. . The possible outcomes of a two class prediction be represented as True positive (TP), True negative (TN), False Positive (FP) and False Negative (FN).
Co-Authors Jagdish S. Shah