Computer-aided diagnosis: automatic detection of malignant masses in digitized mammograms

Abstract

A computerized method to automatically detect malignant masses on digital mammograms based on bilateral subtraction to identify asymmetries between left and right breast images was developed. After the digitization, in order to align left and right mammograms the breast border and nipple were automatically detected. Images were corrected to avoid differences in brightness due to the recording procedure. Left and right mammograms were subtracted and a threshold was applied to obtain a binary image with the information of suspicious areas. The suspicious regions or asymmetries were delimited by a region growing algorithm. Size and eccentricity tests were used to eliminate false-positive responses and texture features were extracted from suspicious regions to reject normal tissue regions. The scheme, tested in 70 pairs of digital mammograms, achieved a true-positive rate of 71% with an average number of 0.67 false positives per image. Computerized detection was evaluated by using free-response operating characteristic analysis (FROC). An area under the AFROC (A1) of 0.667 was obtained. Our results show that the scheme may be helpful to the radiologists by serving as a second reader in mammographic screening. The low number of false positives indicates that our scheme would not confuse the radiologist by suggesting normal regions as suspicious.