Abstract
The usage of internationally acclaimed mammographic databases is important in order to ensure validations and comparison of response from various studies.
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References
C.J. D’Orsi, L.W. Bassett, W.A. Berg, Breast Imaging Reporting and Data System: ACR BI-RADS Mammography, 4th edn. (American College of Radiology, Reston, VA, 2003)
M. Heath, K. Bowyer, D. Kopans, R. Moore, W.P. Kegelmeyer, The digital database for screening mammography, in Proceedings of the 5th International Workshop on Digital Mammography, Toronto Canada, June 2001, ed. by M.I. Yaffe (Medical Physics Publishing, 2001), pp. 212–218
G. Peters, C.M. Jones, K. Daniels, Why is micro-calcification missed on mammography? J. Med. Imaging Radiat. Oncol. 57(1), 32–37 (2013)
J. Suckling, J. Parker, D. Dance, S. Astley, I. Hutt, C. Boggis, I. Ricketts, E. Stamatakis, N. Cerneaz, S. Kok, P. Taylor, D. Betal, J. Savage, The mammographic image analysis society digital mammogram database, in Proceedings of International Congress Series on Excerpta Medica Digital Mammography, U.K., July 1994, vol. 1069, pp. 375–378
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Bhateja, V., Misra, M., Urooj, S. (2020). Mammogram Benchmarking Databases. In: Non-Linear Filters for Mammogram Enhancement. Studies in Computational Intelligence, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-15-0442-6_11
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DOI: https://doi.org/10.1007/978-981-15-0442-6_11
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