Abstract
We present a new associative neural network design especially indicated for the early detection of malignant lesions in breast cancer screening. It is a BAM in which we have made some changes to the functioning of its neurons, and for which we have developed an automatic selection algorithm for the prototypes used to calculate the thresholds of the neurons conforming the input layer. The result is a structure that, while considerably reduced, is highly effective in identifying the images that indicate the presence of malignant tumours in screening for breast cancer. We endowed the network with a special pre-processing stage for the treatment of this kind of radiographic image. This pre-processing yields a more detailed analysis of possible signs of tumours.
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Aligué, F.J.L., Acevedo, I., Orellana, C.G., Macías, M., Velasco, H.G. (2003). Associative Memory for Early Detection of Breast Cancer. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_51
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DOI: https://doi.org/10.1007/978-3-540-44871-6_51
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