Abstract
We are developing a computer-aided detection (CAD) system for masses on digital breast tomosynthesis mammograms (DBT). A data set of DBT from patients was collected with informed consent using a GE prototype DBT system. The system has an Rh/Rh x-ray source and a CsI/a:Si detector, and acquires 21 projection view (PV) images over a 60º arc in 3º increments. The total dose of the 21 PVs is set to be about 1.5 times of the dose of a single screen-film mammogram. In this preliminary study, the DBTs from 50 patients are reconstructed with a simultaneous algebraic reconstruction technique (SART) in two conditions: one using all 21 PVs in 3º increments and the other 11 PVs in 6º increments. The latter therefore uses a subset of the PVs and about half the dose of the former. We compared the mass detection accuracy in these two sets of DBTs using the same CAD system. The system first identifies locations of mass candidates in the DBT volume using 3D gradient field analysis. The mass candidates are then segmented by 3D region growing. Morphological, gray level, and texture features are extracted from the segmented objects. A linear discriminant analysis (LDA) classifier with stepwise feature selection is designed by leave-one-out resampling. The output of the LDA is a mass likelihood score to which a decision threshold is applied and a free-response receiver operating characteristic (FROC) curve is generated. For the DBT set reconstructed with 21 PVs, the system achieved an 80% sensitivity at an average false positive (FP) rate of 1.52 per DBT volume. For the DBT set reconstructed with 11 PVs, the FP rate was 2.38 per breast at the same sensitivity. The difference in the FROC curves for the two conditions was statistically significant (p=0.03) by alternative FROC analysis. When the subset of 14 malignant cases was analyzed, the average FP rates were 0.87 and 1.11 per DBT volume at a sensitivity of 80% for the 21-PV and 11-PV conditions, respectively. The difference in the FROC curves for this smaller subset did not achieve statistical significance.
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Chan, HP., Wei, J., Zhang, Y., Sahiner, B., Hadjiiski, L., Helvie, M.A. (2008). Detection of Masses in Digital Breast Tomosynthesis Mammography: Effects of the Number of Projection Views and Dose. In: Krupinski, E.A. (eds) Digital Mammography. IWDM 2008. Lecture Notes in Computer Science, vol 5116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70538-3_39
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DOI: https://doi.org/10.1007/978-3-540-70538-3_39
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