title: A novel model for smart breast cancer detection in thermogram images.
abstract: Accuracy in feature extraction is an important factor in image classification and retrieval. In this paper, a breast tissue density classification and image retrieval model is introduced for breast cancer detection based on thermographic images. The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrievalwas tested on 400 images. The sensitivity and specificity of the model are 100% and 98%, respectively.
authors.affiliation: Department of Electrical Engineering, Hakim Sabzevari University, Sabzevar, Iran E-mail : imanabaspur@gmail.com.
authors.forename: Iman Abaspur
authors.initials: IA
authors.lastname: Kazerouni
authors.forename: Hossein Ghayoumi
authors.initials: HG
authors.lastname: Zadeh
authors.forename: Javad
authors.initials: J
authors.lastname: Haddadnia
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis; D011379:Prognosis; D012680:Sensitivity and Specificity; D013817:Thermography / Q000379:methods*