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Computerized detection of masses in digital mammograms: Analysis of bilateral subtraction images
Author(s) -
Yin FangFang,
Giger Maryellen L.,
Doi Kunio,
Metz Charles E.,
Vyborny Carl J.,
Schmidt Robert A.
Publication year - 1991
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.596610
Subject(s) - subtraction , artificial intelligence , mammography , computer vision , image subtraction , digital mammography , background subtraction , computer science , feature (linguistics) , digitization , nuclear medicine , mathematics , pattern recognition (psychology) , radiology , medicine , image processing , pixel , image (mathematics) , breast cancer , binary image , linguistics , philosophy , arithmetic , cancer
A computerized scheme is being developed for the detection of masses in digital mammograms. Based on the deviation from the normal architectural symmetry of the right and left breasts, a bilateral subtraction technique is used to enhance the conspicuity of possible masses. The scheme employs two pairs of conventional screen‐film mammograms (the right and left mediolateral oblique views and craniocaudal views), which are digitized by a TV camera/Gould digitizer. The right and left breast images in each pair are aligned manually during digitization. A nonlinear bilateral subtraction technique that involves linking multiple subtracted images has been investigated and compared to a simple linear subtraction method. Various feature‐extraction techniques are used to reduce false–positive detections resulting from the bilateral subtraction. The scheme has been evaluated using 46 pairs of clinical mammograms and was found to yield a 95% true–positive rate at an average of three false–positive detections per image. This preliminary study indicates that the scheme is potentially useful as an aid to radiologists in the interpretation of screening mammograms.