MammoSys: A content-based image retrieval system using breast density patterns.
In this paper, we present a content-based image retrieval system designed to retrieve mammographies from large medical image database. The system is developed based on breast density, according to the four categories defined by the American College of Radiology, and is integrated to the database of the Image Retrieval in Medical Applications (IRMA) project, that provides images with classification ground truth. Two-dimensional principal component analysis is used in breast density texture characterization, in order to effectively represent texture and allow for dimensionality reduction. A support vector machine is used to perform the retrieval process. Average precision rates are in the range from 83% to 97% considering a data set of 5024 images. The results indicate the potential of the system as the first stage of a computer-aided diagnosis framework.
de Oliveira
Júlia E E
JE
Universidade Federal de Minas Gerais, Departamento de Ciência da Computação, Av. Antônio Carlos, 6627, 31270-901, Belo Horizonte, MG, Brazil. julia@dcc.ufmg.br
Machado
Alexei M C
AM
Chavez
Guillermo C
GC
Lopes
Ana Paula B
AP
Deserno
Thomas M
TM
Araújo
Arnaldo de A
Ade A
D022126:Access to Information; D000465:Algorithms; D001185:Artificial Intelligence; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology; D016208:Databases, Factual; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D008327:Mammography / Q000295:instrumentation*; D008962:Models, Theoretical; D025341:Principal Component Analysis