Abstract
With the advent of full-field digital mammography, mammograms may provide a spatial resolution of 0.05 mm pixel size and 12–14 bits of gray level information which corresponds to more than 30 MBytes of data per image. The consequences are increased costs for storage and delays during image communication and display. Image compression techniques offer a solution to these problems [1].
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References
Erickson BJ, Manduca A, Palisson P, Persons KR, Earnest F, Savcenko V, Hangian-dreou NJ (1998) Wavelet compression of medical images. Radiology, 206(3):599–607.
Netsch T (1996) A scale-space approach for the detection of clustered microcalcifications in digital mammograms. In: Doi K, Giger ML, Nishikawa RM, Schmidt RA, editors, Digital Mammography′96, pages 301–306. Elsevier, Amsterdam.
Wallace GK (1991) The JPEG still picture compression standard. Communications of the ACM, 34(4):30–44.
Shapiro JM (1993) Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing, 41(12):3445–3462.
Said A, Pearlman WA (1996) An image multiresolution representation for lossless and lossy compression. IEEE Transactions on Image Processing, 5(9):1303–1310.
Tian J, Wells RO (1996) A lossy image codec based on index coding. In: Proceedings of the IEEE Data Compression Conference, page 456, Snowbird, UT.
Strang G, Nguyen T (1996) Wavelets and filter banks. Wellesley-Cambridge Press, Wellesley, MA.
Villasenor J, Beizer B, Liao J (1995) Wavelet filter evaluation for image compression. IEEE Transactions on Image Processing, 4(8): 1053–1060.
Sharp PF (1990) Quantifying image quality. Clinical physics and physiological measurement, 11:21–26.
Goldberg MA, Pivovarov M, Mayo-Smith WW, Bhalla MP, Blickman JG, Bramson RT, Boland GW, Llewellyn HJ, Halpern E (1994) Application of wavelet compression to digitized radiographs. American Journal of Radiology, 163(2):463–468.
Kjølstad A, Kegelmeyer WP, Sund T, Braathen B (1994) Effects of lossy compression of digital mammograms evaluated by an automatic diagnosis. In: Gale AG, Astley SM, Dance DR, Cairns AY, editors, Digital Mammography, pages 101–110. Elsevier, Amsterdam.
Teo P, Heeger D (1994) Perceptual image distortion. In: Human Vision, Visual Processing, and Digital Display, volume 2179 of SPIE Proceedings, pages 127–142.
Karssemeijer N (1993) Adaptive noise equalization and recognition of microcalcification clusters in mammograms. International Journal of Pattern Recognition and Artificial Intelligence, 7(6): 1357–1376.
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© 1998 Springer Science+Business Media Dordrecht
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Netsch, T., Lang, M., Peitgen, HO. (1998). Automated Detection of Microcalcifications after Lossy Compression of Digital Mammograms. In: Karssemeijer, N., Thijssen, M., Hendriks, J., van Erning, L. (eds) Digital Mammography. Computational Imaging and Vision, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5318-8_77
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DOI: https://doi.org/10.1007/978-94-011-5318-8_77
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