Abstract
Breast density is associated with an increased risk of developing breast cancer, and several methods have been proposed recently for the fully-automatic assessment of volumetric breast density. However, conventional algorithms require an accurate estimation of the breast shape and thickness for the separation into adipose and glandular tissue within the breast. Here, a spectral extension of a recently developed automatic volumetric breast density algorithm is investigated. The proposed approach measures the adipose and glandular tissue content without any additional breast thickness model. The feasibility of the spectral glandularity assessment is illustrated with measurements from an energy-resolving photon-counting mammography system using reference materials including the BR3D phantom.
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References
Alonzo-Proulx, O., Tyson, A.H., Mawdsley, G.E., Yaffe, M.J.: Effect of Tissue Thickness Variation in Volumetric Breast Density Estimation. In: Krupinski, E.A. (ed.) IWDM 2008. LNCS, vol. 5116, pp. 659–666. Springer, Heidelberg (2008)
Åslund, M., Cederström, B., Lundqvist, M., Danielsson, M.: Scatter rejection in multislit digital mammography. Med. Phys. 33, 933–940 (2006)
Boyd, N.F., Martin, L.J., Rommens, J.M., et al.: Mammographic density: a heritable risk factor for breast cancer. Methods Mol. Biol. 472, 343–360 (2009)
Cardinal, H.N., Fenster, A.: An accurate method for direct dual-energy calibration and decomposition. Med. Phys. 17(3), 327–341 (1990)
Ciatto, S., Houssami, N., Apruzzese, A., et al.: Categorizing breast mammographic density: intra- and interobserver reproducibility of BI-RADS density categories. Breast 14(4), 269–275 (2005)
Ciatto, S., Houssami, N., Apruzzese, A., et al.: Reader variability in reporting breast imaging according to BI-RADS assessment categories (the Florence experience). Breast 15(1), 44–51 (2006)
Diffey, J., Hufton, A., Astley, S., Mercer, C., Maxwell, A.: Estimating Individual Cancer Risks in the UK National Breast Screening Programme: A Feasibility Study. In: Krupinski, E.A. (ed.) IWDM 2008. LNCS, vol. 5116, pp. 469–476. Springer, Heidelberg (2008)
Ducote, J.L., Molloi, S.: Scatter correction in digital mammography based on image deconvolution. Phys. Med. Biol. 55(5), 1295–1309 (2010)
Ducote, J.L., Molloi, S.: Quantification of breast density with dual energy mammography: an experimental feasibility study. Med. Phys. 37(2), 793–801 (2010)
van Engeland, S., Snoeren, P.R., Huisman, H., et al.: Volumetric breast density estimation from full-field digital mammograms. IEEE Trans. Med. Imaging 25(3), 273–282 (2006)
Fredenberg, E., Svensson, B., Danielsson, M., et al.: Optimization of mammography with respect to anatomical noise. In: Proc of SPIE, Physics of Medical Imaging, vol. 7961, pp. 796112–11 (2011)
Fredenberg, E., Lundqvist, M., Cederström, B., et al.: Energy resolution of a photon-counting silicon strip detector. Nucl. Instrum. Meth. A 613(1), 156–162 (2010)
Hauge, I.H.R., Hogg, P., Szczepura, K., et al.: The readout thickness versus the measured thickness for a range of screen film mammography and full-field digital mammography units. Med. Phys. 39(1), 263–271 (2012)
Heese, H., Erhard, K., Gooßen, A.: Fully-automatic breast density assessment from full field digital mammograms. In: Proc. Workshop on Breast Image Analysis, pp. 113–120 (2011)
Kallenberg, M.G.J., Lokate, M., van Gils, C.H., Karssemeijer, N.: Automatic breast density segmentation: an integration of different approaches. Phys. Med. Biol. 56(9), 2715–2729 (2011)
Saftlas, A.F., Hoover, R.N., Brinton, L.A., et al.: Mammographic densities and risk of breast cancer. Cancer 67(11), 2833–2838 (1991)
Shepherd, J.A., Kerlikowske, K.M., Smith-Bindman, R., et al.: Measurement of breast density with dual X-ray absorptiometry: feasibility. Radiology 223(2), 554–557 (2002)
Snoeren, P.R., Karssemeijer, N.: Thickness correction of mammographic images by means of a global parameter model of the compressed breast. IEEE Trans. Med. Imaging 23(7), 799–806 (2004)
Tromans, C., Brady, M.: An Alternative Approach to Measuring Volumetric Mammographic Breast Density. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds.) IWDM 2006. LNCS, vol. 4046, pp. 26–33. Springer, Heidelberg (2006)
U.S. Connecticut Senate (ed.): Bill No. 458. Public Act No. 09-41 (2009)
Wolfe, J.N.: Breast patterns as an index of risk for developing breast cancer. AJR Am. J. Roentgenol. 126(6), 1130–1137 (1976)
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Gooßen, A., Heese, H.S., Erhard, K., Norell, B. (2012). Spectral Volumetric Glandularity Assessment. In: Maidment, A.D.A., Bakic, P.R., Gavenonis, S. (eds) Breast Imaging. IWDM 2012. Lecture Notes in Computer Science, vol 7361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31271-7_68
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DOI: https://doi.org/10.1007/978-3-642-31271-7_68
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