24 June 1998 Medical image processing using neural networks based on multivalued and universal binary neurons
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Abstract
Cellular Neural Networks (CNN) has become a very good mean for solution of the different kind of image processing problems. CNN based on multi-valued neurons (CNN-MVN) and CNN based on universal binary neurons (CNN-UBN) are the specific kinds of the CNN. MVN and UBN are neurons with complex-valued weights, and complex internal arithmetic. Their main feature is possibility of implementation of the arbitrary mapping between inputs and output described by the MVN, and arbitrary (not only threshold) Boolean function (UBN). Great advantage of the CNN is possibility of implementation of the any linear and many non-linear filters in spatial domain. Together with noise removing using CNN it is possible to implement filters, which can amplify high and medium frequencies. These filters are a very good mean for solution of the enhancement problem, and problem of details extraction against complex background. So, CNN make it possible to organize all the processing process from filtering until extraction of the important details. Organization of this process for medical image processing is considered in the paper. A major attention will be concentrated on the processing of the x-ray and ultrasound images corresponding to different oncology (or closed to oncology) pathologies. Additionally we will consider new structure of the neural network for solution of the problem of differential diagnostics of breast cancer.
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Igor N. Aizenberg, Igor N. Aizenberg, Naum N. Aizenberg, Naum N. Aizenberg, Eugen S. Gotko, Eugen S. Gotko, Vladimir A. Sochka, Vladimir A. Sochka, } "Medical image processing using neural networks based on multivalued and universal binary neurons", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310966; https://doi.org/10.1117/12.310966
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