title: Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.
abstract: In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.
authors: Indian Institute of Information Technology and Management, Morena Link Road, Gwalior, India.
authors: Arpita
authors: A
authors: Das
authors: Mahua
authors: M
authors: Bhattacharya
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000000981:diagnostic imaging*; D019295:Computational Biology; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data*; D011856:Radiographic Image Enhancement / Q000379:methods*