International Journal of Advanced Research and Development

ISSN: 2455-4030

Vol. 1, Issue 8 (2016)

A formulated analysis of pattern recognition technical approach on various research oriented medical applications

Author(s): Hariharasudhan S, Dr. Raghu B
Abstract: Pattern Recognition aims to extract meaningful data from the medical image to organize its application oriented contents. It is the research area that studies the process and design of systems to identify patterns in data and has fascinated the awareness of researchers in last many decades as a machine mechanism learning approach due to its extensive spread of application areas. The application area includes Medicine, Data mining, modern Communications, Military intelligence, Bioinformatics, Automations, Document classification, Speech recognition, Business oriented and others. The identification of the pattern in an image can be described efficiently and effectively with the mode of Pattern Recognition (PR) techniques. A pattern recognition technique intimates that how machines can monitor the image, gain knowledge to differentiate patterns from their background. Pattern recognition design can be considered using the following main approaches of Structural Techniques, Statistical Techniques, Fuzzy Model, Template Matching, Hybrid Models and Neural Network. This paper is mainly concentrated on the formulated analysis of pattern recognition technical approaches of Statistical on research oriented medical applications. Pattern Recognition techniques are acknowledged as practical tools in the service of diagnosis in clinical resolution making. Here the Statistical pattern recognition approach focuses on the statistical properties of the medical image patterns and the effectiveness of statistical pattern recognition system is associated with the medical application oriented implementation of the classification and description tasks. The goal of this research paper is to analyze the problematical mechanisms of research oriented medical applications by Pattern Recognition technical approaches.
Pages: 45-47  |  1029 Views  289 Downloads
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