UGC Approved Journal no 63975(19)

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

Volume 5 Issue 7
July-2018
eISSN: 2349-5162

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

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Published Paper ID:
JETIR1807759


Registration ID:
185613

Page Number

272-278

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Title

BRAIN TUMOR HYBRID SFC TECHNIQUE FOR SEGMENTATION USING K-MEANS CLUSTERING FROM MRI USING DWT & PCA FOR FEATURE EXTRACTION AND NN FOR CLASSIFICATION

Abstract

An abnormal growth of cells in the brain is called a brain tumor. A brain tumor consists of a collection of abnormally functioning brain cells that have begun to grow and reproduce inappropriately. The uncontrolled growth of group of cells compresses and damages normal brain structures, which causes a variety of neurological symptoms. According to the reports of National Cancer Institute, Primary brain tumors are the leading cause of tumor cancer deaths in children, now surpassing acute lymphoblast leukemia and are the third leading cause of cancer death in young adults ages 20 to 39. There are more than 120 different types of brain tumors, making effective treatment very complicated. As per classification system defined by World Health Organization (WHO), brain tumor is named for the cell type of origin. Brain tumors can either originate from within the brain or from cancer cells that have metastasized from other organs or tissues. Various techniques are developed in the past to detect brain tumor. This research work proposed a Brain tumor Hybrid SFC Technique for segmentation using K-means Clustering from MRI using DWT & PCA for Feature Extraction and SVM for Classification.

Key Words

brain tumor, magnetic resonance imaging segmentation, pca, glcm..

Cite This Article

"BRAIN TUMOR HYBRID SFC TECHNIQUE FOR SEGMENTATION USING K-MEANS CLUSTERING FROM MRI USING DWT & PCA FOR FEATURE EXTRACTION AND NN FOR CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.272-278, July-2018, Available :http://www.jetir.org/papers/JETIR1807759.pdf

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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

"BRAIN TUMOR HYBRID SFC TECHNIQUE FOR SEGMENTATION USING K-MEANS CLUSTERING FROM MRI USING DWT & PCA FOR FEATURE EXTRACTION AND NN FOR CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp272-278, July-2018, Available at : http://www.jetir.org/papers/JETIR1807759.pdf

Publication Details

Published Paper ID: JETIR1807759
Registration ID: 185613
Published In: Volume 5 | Issue 7 | Year July-2018
DOI (Digital Object Identifier):
Page No: 272-278
Country: Hoshiarpur, Punjab, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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