title: Multi-View Probabilistic Classification of Breast Microcalcifications.
abstract: Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we apply a multi-view-classifier for the task. We describe a two-step classification method that is based on a view-level decision, implemented by a logistic regression classifier, followed by a stochastic combination of the two view-level indications into a single benign or malignant decision. The proposed method was evaluated on a large number of cases from a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the advantage of the proposed multi-view classification algorithm that automatically learns the best way to combine the views.
authors.forename: Alan Joseph
authors.initials: AJ
authors.lastname: Bekker
authors.forename: Moran
authors.initials: M
authors.lastname: Shalhon
authors.forename: Hayit
authors.initials: H
authors.lastname: Greenspan
authors.forename: Jacob
authors.initials: J
authors.lastname: Goldberger
mesh_terms: D000465:Algorithms; D001940:Breast / Q000000981:diagnostic imaging; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*