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Proceedings Paper

Comparison of computerized mass detection in digital breast tomosynthesis (DBT) mammograms and conventional mammograms
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Paper Abstract

We are developing a CAD system for mass detection on digital breast tomosynthesis (DBT) mammograms. In this study, we compared the detection accuracy on DBT and conventional screen-film mammograms (SFMs). DBT mammograms were acquired with a GE prototype system at the University of Michigan. 47 cases containing the CC- and MLO-view DBT mammograms of the breast with a biopsy-proven mass and the corresponding two-view SFMs of the same breast were collected. Subjective judgment showed that the masses were much more conspicuous on DBT slices than on SFMs. The CAD system for DBT includes two parallel processes, one performs mass detection in the reconstructed DBT volume, and the other in the projection view (PV) images. The mass likelihood scores estimated for each mass candidate in the two processes are merged to differentiate masses and false positives (FPs). For detection on SFMs, we previously developed a dual system approach by fusing two single CAD systems optimized for detection of average and subtle masses, respectively. A trained neural network is used to merge the mass likelihood scores of the two single systems to reduce FPs. At the case-based sensitivities of 80% and 85%, mass detection in the DBT volume resulted in an average of 0.72 and 1.06 FPs/view, and detection in the SFMs yielded 0.94 and 1.67 FPs/view, respectively. The difference fell short of statistical significance (p=0.07) by JAFROC analysis. Study is underway to collect a larger data set and to further improve the DBT CAD system.

Paper Details

Date Published: 3 March 2009
PDF: 7 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72600S (3 March 2009); doi: 10.1117/12.813851
Show Author Affiliations
Heang-Ping Chan, Univ. of Michigan (United States)
Jun Wei, Univ. of Michigan (United States)
Berkman Sahiner, Univ. of Michigan (United States)
Lubomir Hadjiiski, Univ. of Michigan (United States)
Mark A. Helvie, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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