Abstract
For over ten years, we have been developing automated computerized schemes to assist radiologists in detecting breast cancer from mammograms. These detection schemes have been implemented on an “intelligent” mammography workstation that has been used prospectively on screening mammograms for over three years. The purpose of this study was to analyze the performance of the workstation in comparison to radiologists’ clinical interpretations of the same screening mammograms.
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References
Yin F-F, Giger ML, Doi K, Metz CE, Vyborny CJ, Schmidt RA (1991) Computerized detection of masses in digital mammograms: Analysis of bilateral subtraction images. Medical Physics 18, pp 955–963.
Yin F-F, Giger ML, Doi K, Vyborny CJ, Schmidt RA (1992) Computerized detection of masses in digital mammograms: Automated alignment of breast images and its effect on bilateral-subtraction technique. Medical Physics pp
Kupinski M, Giger ML, Lu P, Huo Z (1995) Computerized detection of mammographic lesions: Performance of artificial neural network with enhanced feature extraction. Proc SPIE 2434, pp 598–605.
Chan H-P, Doi K, Vyborny CJ, Metz CE, MacMahon H, Jokich P, Galhotra S (1987) Digital mammography: Development of a computer-aided system for detection of microcalcifications. Proc SPIE 767, pp 367–370.
Chan H-P, Doi K, Vyborny CJ, Lam KL, Schmidt RA (1988) Computer-aided detection of microcalcifications in mammograms: Methodology and preliminary clinical study. Investigative Radiology 23, pp 664–671.
Chan H-P, Doi K, Vyborny CJ, Schmidt RA, Metz CE, Lam KL, Ogura T, Wu Y, MacMahon H (1990) Improvement in radiologists’ detection of clustered microcalcifications on mammograms: The potential of computer-aided diagnosis. Investigative Radiology 25, pp 1102–1110.
Ema T, Doi K, Nishikawa RM, Jiang Y, Papaioannou J (1995) Image feature analysis and computer-aided diagnosis in mammography: Reduction of false-positive clustered microcalcifications using local edge-gradient analysis. Medical Physics 22, pp 161–169.
Nishikawa RM, Giger ML, Doi K, Vyborny CJ, Schmidt RA (1995) Computer-aided detection of clustered microcalcifications using digital mammograms. Medicine and Biology in Engineering and Computing 33, pp 174–178.
Nishikawa RM, Jiang Y, Giger ML, Schmidt RA, Vyborny CJ, Zhang W, Papaioannou J, Bick U, Nagel RH, Doi K (1994) Performance of automated CAD schemes for the detection and diagnosis of clustered microcalcifications. In: Gale AG, Astley SM, Dance DR, Cairns AY, (eds.), Digital Mammography. Elsevier Publishing, Amsterdam, pp 13–20.
Zhang W, Doi K, Giger ML, Nishikawa RM, Schmidt RA (1996) An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms. Medical Physics 23, pp 595–601.
Schmidt RA, Nishikawa RM, Osnis R, Schreibman KL, Giger ML, Doi K (1996) Computerized detection of lesions missed by mammography. In: Doi K, Giger ML, Nishikawa RM, Schmidt RA, (eds.), Digital Mammography’ 96. Elsevier Science, Amsterdam, pp 105–110.
te Brake GM, Karssemeijer N, Hendriks JHCL (1998) Automated detection of breast carcinomas not detected in a screening program. Radiology 207, pp 465–471.
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© 1998 Springer Science+Business Media Dordrecht
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Nishikawa, R.M. et al. (1998). Prospective Testing of a Clinical Mammography Workstation for CAD: Analysis of the First 10,000 Cases. 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_65
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DOI: https://doi.org/10.1007/978-94-011-5318-8_65
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