Abstract
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.
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References
Singh, S., Tourassi, G.D., Baker, J.A., Samei, E., Lo, J.Y.: Automated breast mass detection in 3D reconstructed tomosynthesis volumes: a featureless approach. Med. Phys. 35(8), 3626–3636 (2008)
Reiser, I., Nishikawa, R.M., Giger, M.L., Wu, T., Rafferty, E.A., Moore, R., Kopans, D.B.: Computerized mass detection for digital breast tomosynthesis directly from the projection images. Med. Phys. 33(2), 482–491 (2006)
Chan, H.P., Wei, J., Zhang, Y., Helvie, M.A., Moore, R.H., Sahiner, B., Hadjiiski, L., Kopans, D.B.: Computer-aided detection of masses in digital tomosynthesis mammography: comparison of three approaches. Med. Phys. 35(9), 4087–4095 (2008)
Kallenberg, M., Karssemeijer, N.: Computer-aided detection of masses in full-field digital mammography using screen-film mammograms for training. Phys. Med. Biol. 53(23), 6879–6891 (2008)
Karssemeijer, N.: Automated classification of parenchymal patterns in mammograms. Phys. Med. Biol. 43(2), 365–378 (1998)
Karssemeijer, N., Te Brake, G.M.: Detection of stellate distortions in mammograms. IEEE Trans Med. Imaging 15(5), 611–619 (1996)
te Brake, G.M., Karssemeijer, N.: Single and multiscale detection of masses in digital mammograms. IEEE Trans Med. Imaging 18(7), 628–639 (1999)
Timp, S., Karssemeijer, N.: A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography. Med. Phys. 31(5), 958–971 (2004)
te Brake, G.M., Karssemeijer, N., Hendriks, J.H.: An automatic method to discriminate malignant masses from normal tissue in digital mammograms. Phys. Med. Biol. 45(10), 2843–2857 (2000)
Hupse, R., Karssemeijer, N.: Use of normal tissue context in computer-aided detection of masses in mammograms. IEEE Trans Med. Imaging 28(12), 2033–2041 (2009)
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van Schie, G., Leifland, K., Wallis, M., Moa, E., Hemmendorff, M., Karssemeijer, N. (2010). The Effect of Slab Size on Mass Detection Performance of a Screen-Film CAD System in Reconstructed Tomosynthesis Volumes. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds) Digital Mammography. IWDM 2010. Lecture Notes in Computer Science, vol 6136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13666-5_67
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DOI: https://doi.org/10.1007/978-3-642-13666-5_67
Publisher Name: Springer, Berlin, Heidelberg
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