title: Discovering mammography-based machine learning classifiers for breast cancer diagnosis.
abstract: This work explores the design of mammography-based machine learning classifiers (MLC) and proposes a new method to build MLC for breast cancer diagnosis. We massively evaluated MLC configurations to classify features vectors extracted from segmented regions (pathological lesion or normal tissue) on craniocaudal (CC) and/or mediolateral oblique (MLO) mammography image views, providing BI-RADS diagnosis. Previously, appropriate combinations of image processing and normalization techniques were applied to reduce image artifacts and increase mammograms details. The method can be used under different data acquisition circumstances and exploits computer clusters to select well performing MLC configurations. We evaluated 286 cases extracted from the repository owned by HSJ-FMUP, where specialized radiologists segmented regions on CC and/or MLO images (biopsies provided the golden standard). Around 20,000 MLC configurations were evaluated, obtaining classifiers achieving an area under the ROC curve of 0.996 when combining features vectors extracted from CC and MLO views of the same case.
authors.affiliation: Center of Extremadura for Advanced Technologies, Trujillo, Spain. raul.ramos@ciemat.es
authors.forename: Raúl
authors.initials: R
authors.lastname: Ramos-Pollán
authors.forename: Miguel Angel
authors.initials: MA
authors.lastname: Guevara-López
authors.forename: Cesar
authors.initials: C
authors.lastname: Suárez-Ortega
authors.forename: Guillermo
authors.initials: G
authors.lastname: Díaz-Herrero
authors.forename: Jose Miguel
authors.initials: JM
authors.lastname: Franco-Valiente
authors.forename: Manuel
authors.initials: M
authors.lastname: Rubio-Del-Solar
authors.forename: Naimy
authors.initials: N
authors.lastname: González-de-Posada
authors.forename: Mario Augusto Pires
authors.initials: MA
authors.lastname: Vaz
authors.forename: Joana
authors.initials: J
authors.lastname: Loureiro
authors.forename: Isabel
authors.initials: I
authors.lastname: Ramos
mesh_terms: D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000145:classification* / Q000175:diagnosis*; D003199:Computer Systems; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008327:Mammography / Q000379:methods*