UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 2 Issue 3
March-2015
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR1503090


Registration ID:
150279

Page Number

851-854

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Title

Classification of MRI Brain Image using SVM Classifier

Abstract

In this paper we describe the design and development of content-based image retrieval (CBIR) system. This system enables both multi-image query and slide –level image retrieval in order to protect the semantic consistency among the retrieved images. Content of image retrieval is the process of finding relevant image from large collection of image database using visual queries. Medical images have led to growth in large image collection. To enhance the medical image retrieval for diagnostics, research and teaching purposes is done by CBIR. The system performance is improved by the multiple image queries instead of single image query. Pre-processing of the query image is done by median filter to remove the noise. Then the filtered image is given as input to the feature extraction technique which is a transformation of input image into set of features such as texture and shape. Feature extraction is done by the Gray level co-occurrence matrix algorithm that contains information about the position of pixels having similar gray level values. SVM (Support Vector machine) classifier is to group items that have similar feature values into three categories such as normal, benign and malignant. Then SVM classifier is followed by KNN (K-nearest neighbour) which search the corresponding database index will be computed by similarity feature matching. The query image is classified by the classifier to a particular class and the relevant images are retrieved from the database.

Key Words

Feature Extraction, GLCM, Image Retrieval, MRI, SVM Classifier

Cite This Article

"Classification of MRI Brain Image using SVM Classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 3, page no.851-854, March-2015, Available :http://www.jetir.org/papers/JETIR1503090.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Classification of MRI Brain Image using SVM Classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 3, page no. pp851-854, March-2015, Available at : http://www.jetir.org/papers/JETIR1503090.pdf

Publication Details

Published Paper ID: JETIR1503090
Registration ID: 150279
Published In: Volume 2 | Issue 3 | Year March-2015
DOI (Digital Object Identifier):
Page No: 851-854
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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