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Computer aided detection of masses in mammograms as decision support

Radboud University Nijmegen Medical Centre, ¹ Department of Radiology, ² Department of Epidemiology and Biostatistics and ³ National Expert and Training Centre for Breast Cancer Screening, Nijmegen, The Netherlands

Correspondence: Nico Karssemeijer, Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. E-mail: n.karssemeijer{at}rad.umcn.nl

Performance of a computer aided detection (CAD) system for masses in mammograms was investigated. Using data collected in an observer study, in which experienced screening radiologists read a series of 500 screening mammograms without CAD, performance of radiologists was compared to the standalone performance of the CAD system. Due to a larger number of FPs (false positives), the performance of CAD was lower than that of the readers. However, when analysis was restricted to mammographic regions identified by the radiologists, it was found that the CAD system was comparable to the readers in discriminating these regions in cancer and non-cancer. In a retrospective analysis, the effect of independent combination of reader scores with CAD was compared to independent combination of scores of two radiologists. No significant difference was found between the results of these two methods. Both methods improved single reading results significantly.