FDDSM: Toward a full field digital mammographic database

Computer-Aided Detection and Diagnosis (CADD) systems have been created in the last two decades to help radiologists either in the automatic detection or diagnosis of abnormalities in mammographic images. Accordingly, the developed algorithms in an existing amount of mammographic images should be assessed on a large database. For a fair validation, the database should be very representative including different subjects and anomalies. Nevertheless, available mammographic images databases do not provide the required resolution quality and are not well covering all kinds of diseases such as architectural distortion and kists. They also lack some important subject details such as biopsy results, hereditary factors, etc..., thus making critical the generalization of research results. In this paper, we present a new mammographic image database Farabi Digital Database of Screening Mammography (FDDSM), collected in El Farabi radiology center. The digitization of mammographic images was made with high contrast and a resolution of 12 bits per pixel. The database covers 2052 mammograms for 342 subjects. It was collected on a three year time period. As illustration, the presented database was used, in previous work, for mass detection and classification and achieves good generalization performances.