International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 82 - Issue 15 |
Published: November 2013 |
Authors: Venkata Ragha Deepthi Loka, Sudhakar Putheti |
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Venkata Ragha Deepthi Loka, Sudhakar Putheti . Classification of Normal, Benign and Malignant Tissues using Fuzzy Texton and Support Vector Machine in Mammographic Images. International Journal of Computer Applications. 82, 15 (November 2013), 36-39. DOI=10.5120/14243-2450
@article{ 10.5120/14243-2450, author = { Venkata Ragha Deepthi Loka,Sudhakar Putheti }, title = { Classification of Normal, Benign and Malignant Tissues using Fuzzy Texton and Support Vector Machine in Mammographic Images }, journal = { International Journal of Computer Applications }, year = { 2013 }, volume = { 82 }, number = { 15 }, pages = { 36-39 }, doi = { 10.5120/14243-2450 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2013 %A Venkata Ragha Deepthi Loka %A Sudhakar Putheti %T Classification of Normal, Benign and Malignant Tissues using Fuzzy Texton and Support Vector Machine in Mammographic Images%T %J International Journal of Computer Applications %V 82 %N 15 %P 36-39 %R 10.5120/14243-2450 %I Foundation of Computer Science (FCS), NY, USA
Content Based Image Retrieval systems are helpful to the radiologists in diagnosis of breast cancer. This paper presents a method for retrieving breast tissue as normal, benign or malignant in mammograms by using FuzzyTextons. In feature extraction first fuzzy texton images of mammograms are calculated. During the detection of fuzzy texton, fuzzy based quantization is performed to get more accurate textons. Then feature vectors are extracted for fuzzy textons and for efficient classification and retrieval Support Vector Machine is used. The proposed method was tested for a mammogram set from MIAS database.