In the development of a computer-aided detection (CAD) system a large database of training samples is of major importance. However digital breast tomosynthesis (DBT) is a relatively new modality and no large database of cases is available yet. To overcome this limitation we are developing a CAD system for mass detection in DBT that can be trained with regular 2D mammograms, for which large datasets are available. We trained our system with a very large database of screen-film mammograms (SFM). Our approach does not use projection images, but only reconstructed volumes, because it is expected that manufacturers of tomosynthesis systems will only store the reconstructed volumes. In this study we developed a method that converts reconstructed volumes into a series of SFM-like slices and combinations of slices, called slabs. By combining slices into slabs, more information of a whole mass, which usually spans several slices, is used and its appearance becomes more similar to a 2D mammogram. In this study we investigate the effect of using slabs of different sizes on the performance of our CAD system. For validation we use a dataset of 63 tomosynthesis cases (245 volumes) consisting of 42 normal cases (163 volumes) and 21 abnormal cases (82 volumes) with a total of 47 malignant masses and architectural distortions. The volumes are acquired with a tomosynthesis system from Sectra and are reconstructed into 0.3 cm thick slices. Results show that performance of our CAD system increases significantly when slices are combined into larger slabs. Best performance is obtained when a slab thickness of 1.5 cm (5 slices) is used, which is significantly higher than using slabs of a single slice, two slices and all slices.
The Effect of Slab Size on Mass Detection Performance of a Screen-Film CAD System in Reconstructed Tomosynthesis Volumes
G. van Schie, M. K. Leifland, E. Moa, M. Hemmendorff and N. Karssemeijer
IWDM '10: Proceedings of the 10th international workshop on Digital Mammography 2010:497-504.