Title :
Mass detection in mammograms using GA based PCA and Haralick features selection
Author :
Amroabadi, S.H. ; Ahmadzadeh, M.R. ; Hekmatnia, A.
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Toronto, Toronto, ON, Canada
Abstract :
Many existing researches utilized different types of feature extraction techniques to detect masses in ROI images. Based on our observations, inclusion of additional features beyond a certain point worsens the performance rather than enhancing it. This paper describes a hybrid method of mammogram recognition which is based on principle component analysis, Haralick features and Genetic algorithm to select the best features.
Keywords :
cancer; diagnostic radiography; feature extraction; genetic algorithms; mammography; medical image processing; principal component analysis; GA based PCA; Haralick feature selection; ROI images; feature extraction techniques; genetic algorithm; hybrid method; mammogram mass detection; mammogram recognition; principal component analysis; Digital mammography; Genetic algorithm; Principle Component Analysis; cooccurrence matrices;
Conference_Titel :
Electrical Engineering (ICEE), 2011 19th Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4577-0730-8