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Associative Memory for Early Detection of Breast Cancer

机译:用于早期检测乳腺癌的关联记忆

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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.
机译:我们提出了一种新的联想神经网络设计,特别是在乳腺癌筛查中早期发现恶性病变的早期发现。这是一个BAM,我们已经对其神经元的运作进行了一些改变,我们已经开发了用于计算符合输入层的神经元阈值的原型的自动选择算法。结果是一种结构,虽然显着降低,但在鉴定表明筛选乳腺癌中存在恶性肿瘤的图像的图像非常有效。我们以特殊的预处理阶段赋予了网络的特殊预处理阶段,用于治疗这种放射线图像。这种预处理产生了对肿瘤可能迹象的更详细分析。

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