Abstract
A previously developed computerized scheme to detect masses has been further revised and several improvements were intended. Mammograms were digitized at a higher resolution with a mammographic laser scanner providing 12 bits. Some steps of the scheme, based on bilateral subtraction technique, were modified. Several new features were designed and a BPN neural network was used to reduce the number of false positives. Results obtained with the training set were encouraging, yielding a sensitivity of 85% and 1.54 mean number of false positives per image before applying false positive reduction. After applying false positive reduction, a sensitivity of 78.3% at a mean number of 0.4 false positives per image was obtained. The area under the AFROC curve was A1 = 0.808.
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References
Sickles, E. A.: Mammographic features of early breast cancer. Ameriacan Journal of Roentgenology 143 (1984) 461–464
Tabar, L., Dean, P. B.: Teaching Atlas of Mammography. Georg Thieme Verlag/ Thieme, Sttugart (1985)
Feig, S. A.: Decreased breast cancer mortality through mammographic screening: results of clinical trials. Radiology 167 (1988) 659–665
Bird, R. E., Wallace, T. W., Yankaskas, B. C.,: Analysis of cancers missed at screening mammography. Radiology 184 (1992) 613–617
Kegelmeyer, W. P., Pruneda, J. M., Bourland, P. D., Hillis, A., Riggs, M. W., Nipper, M. L.: Computer-aided mammographic screening for spiculated lesions. Radiology 191 (1994) 331–337
Méndez, A.J., Tahoces, P.G., Lado, M.J., Souto, M., Vidal, J.J.: Computer-aided diagnosis: Automatic detection of malignant masses in digitized mammograms. Medical Physics 25 (1998) 957–964
Lado, M.J., Tahoces, P.G., Méndez, A.J., Souto, M., Vidal, J.J.: A wavelet-based algorithm for detecting clustered microcalcifications in digital mammograms. Medical Physics 26 (1999) 1294–1305
Winsberg, F., Elkin, M., Macy, J., Bordaz, V, Weymouth, W.: Detection of radiographic abnormalities in mammograms by means of optical scanning and computer analysis. Radiology 89 (1967) 211–215
Yin, F. F., Giger, M. L., Doi, K., Metz, C. E., Vyborny, C. J., Schmidt R. A.: Computerized detection of masses in digital mammograms: analysis of bilateralsubtraction images. Medical Physics 18 (1991) 955–963
Chakraborty, D.P., Winter, L.H.L.: Free-response methodology: Alternate analysis and a new observer-performance experiment. Radiology 174 (1990) 873–881
Méndez, A.J., Tahoces, P.G., Lado, M.J., Souto, M., Correa, J., Vidal, J.J.: Automatic detection of breast border and nipple in digital mammograms. Computer Methods and Programs in Biomedicine 49 (1996) 253–262
Zheng, B., Chang, Y.-H., Gur, D.: Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis. Academic Radiology 2 (1995) 959–966
Doi, T., Hasegawa, A., Hunt. B., Marshall, J., Rao, F., Roehrig, J., Romsdahl, H., Schneider, A., Sharbaugh, R., Wang, B., Zhang, W.: Clinical Results with the R2 ImageChecker Mammographic CAD System. Computer-Aided Diagnosis in Medical Imaging, Elsevier Science (1999)
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Méndez, A.J., Tahoces, P.G., Varela, C., Lado, M.J., Souto, M., Vidal, J.J. (2001). Improvement of a Mammographic CAD System for Mass Detection. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_27
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DOI: https://doi.org/10.1007/3-540-45497-7_27
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