Abstract
In this paper we present a novel approach for microcalcification detection in Digital Breast Tomosynthesis (DBT) datasets. A reconstruction-independent approach, working directly on the projected views, is proposed. Wavelet filter responses on the projections are thresholded and combined to obtain candidate microcalcifications. For each candidate, we create a fuzzy contour through a multi-level thresholding process. We introduce a fuzzy set definition for the class microcalcification contour that allows the computation of fuzzy membership values for each candidate contour. Then, an aggregation operator is presented that combines information over the complete set of projected views, resulting in 3D fuzzy particles. A final decision is made taking into account information acquired over a range of successive processing steps. A clinical example is provided that illustrates our approach. DBT still being a new modality, a similar published approach is not available for comparison and limited clinical data currently prevents a clinical evaluation of the algorithm. .
Keywords
- Digital Mammography
- Aggregation Operator
- Digital Breast Tomosynthesis
- Algebraic Reconstruction Technique
- Projected View
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Kerlikowske, K., Schipper, H.: Fast Facts-Breast Cancer (Epidemiology). Health Press Limited, Oxford (1998)
Holland, T., et al.: So-called interval cancers of the breast: pathologic and radiographic analysis. Cancer 49, 2527–2533 (1982)
Dobbins III, J.T., Godfrey, D.J.: Digital x-ray tomosynthesis: current state of the art and clinical potential. Physics in Medicine and Biology 48, R65–R106 (2003)
Wu, T., Stewart, A., Stanton, M., McCauley, T., Phillips, W., Kopans, D.B., Moore, R.H., Eberhard, J.W., Opsahl-Ong, B., Niklason, L., Williams, M.B.: Tomo-graphic mammography using a limited number of low-dose cone-beam projection images. Medical Physics 30, 365–380 (2003)
Lanyi, M.: Diagnosis and Differential Diagnosis of Breast Calcifications. Springer, Heidelberg (1988)
Chan, H.-P., Wei, J., Sahiner, B., Rafferty, E.A., Wu, T., Roubidoux, M.A., Moore, R.H., Kopans, D.B., Hadjiiski, L.M., Helvie, M.A.: Computerized Detection of Masses on Digital Tomosynthesis Mammograms - A preliminary Study. In: Proceedings of the 7th International Workshop on Digital Mammography, Chapel Hill, NC. Springer, Heidelberg (2004)
Reiser, I., Nishikawa, R.M., Giger, M.L., Kopans, D.B., Rafferty, E.A., Moore, R., Wu, T.: A Reconstruction-Independent Method for Computerized Detection of Mammographic Masses in Tomosynthesis Images. In: Proceedings of the 7th International Workshop on Digital Mammography, Chapel Hill, NC. Springer, Heidelberg (2004)
Cheng, H.D., Lui, Y.M., Freimanis, R.I.: A novel Approach to Microcalcification Detection Using Fuzzy Logic Technique. IEEE Transactions on Medical Imaging 17(3), 442–450 (1998)
Bothorel, S., Bouchon-Meunier, B., Muller, S.: A Fuzzy Logic Based Approach for Semiological Analysis of Microcalcifications in Mammographic Images. International Journal for Intelligent Systems 12, 819–848 (1997)
Pandey, N., Salcic, Z., Sivaswamy, J.: Fuzzy Logic Based Microcalcification Detection. In: Neural Networks for Signal Processing - Proceedings of the IEEE Work-shop, vol. 2, pp. 662–671 (2000)
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Peters, G., Muller, S., Bernard, S., Iordache, R., Wheeler, F., Bloch, I. (2005). Reconstruction-Independent 3D CAD for Calcification Detection in Digital Breast Tomosynthesis Using Fuzzy Particles. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_42
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DOI: https://doi.org/10.1007/11578079_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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