1. Arbach, L., Bennett, D.L., Reinhardt, J.M., Fallouh, G.: Classification of mammographic masses: comparison between backpropagation neural network (BNN) and human readers. Department of Biomedical Engineering. The University of Iowa. Iowa City. IA 52242 USA. Department of Radiology. The University of Iowa. Iowa City. Department of Biomedical Engineering. Damascus University (2003)
2. Collins, C.: Breast cancer detection aided by new technology installed at Magee-Womens Hospital of University of Pittsburgh Medical Center. Pittsburgh, Magee Womens Hospital (2002)
3. Fahlman, S.E., Labiere, C.: The cascade-correlation learning architecture. In: Touretzky, D. (ed.) Advances in NIPS2, pp. 524–532. Carneige-Mellon University, Pittsburgh (1990)
4. Kim, J., Park, H.: Statistical textural features for detection of microcalcifications in digitized mammograms. IEEE Trans. Medical Imag. 18, 231–238 (1999)
5. Kuo, W., Chang, R.F., Moon, W.K., Lee, C.C., Chen, D.R.: Computer-aided diagnosis of breast tumors with different US systems. Acad. Radiol. 9(7), 793–799 (2002)