DocumentCode :
497818
Title :
Mammogram tumor classification using multimodal features and Genetic Algorithm
Author :
Suganthi, M. ; Madheswaran, M.
Author_Institution :
Dept. of Electron. & Commun. Eng., Muthayammal Eng. Coll., Rasipuram, India
fYear :
2009
fDate :
4-6 June 2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper proposes a computer aided decision support system for an automated diagnosis and classification of breast tumor using mammogram. The proposed method differentiates two breast diseases namely benign masses and malignant tumors. From the preprocessed mammogram image, texture and shape features are extracted. The optimal features can be extracted by using a feature selection scheme based on the multi objectives genetic algorithm (MOGA).The performance of the proposed method is compared with the previous methods in terms of classification accuracy, training and testing time. Simulation results show that, this approach is an efficient, easy to use and can achieve high sensitivity.
Keywords :
genetic algorithms; image texture; mammography; medical diagnostic computing; medical image processing; tumours; automated diagnosis; benign masses; breast diseases; breast tumor; computer aided decision support system; image texture; malignant tumors; mammogram tumor classification; multimodal features; multiobjectives genetic algorithm; Benign tumors; Breast neoplasms; Breast tumors; Decision support systems; Diseases; Feature extraction; Genetic algorithms; Malignant tumors; Shape; Testing; MOGA Classification; Mammogram; Shape features; Texture features;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation, Communication and Energy Conservation, 2009. INCACEC 2009. 2009 International Conference on
Conference_Location :
Perundurai, Tamilnadu
Print_ISBN :
978-1-4244-4789-3
Type :
conf
Filename :
5204384
Link To Document :
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