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Computer-Aided Diagnosis System with Backpropagation Artificial Neural Network-Improving Human Readers Performance

机译:计算机辅助诊断系统,具有背部化人工神经网络 - 改善人类读者表现

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This article presents the results of a study into possibility of artificial neural networks (ANNs) to classify cancer changes in mammographic images. Today's Computer-Aided Detection (CAD) systems cannot detect 100 % of pathological changes. One of the properties of an ANN is generalized information -it can identify not only learned data but also data that is similar to training set. The combination of CAD and ANN could give better result and help radiologists to take the right decision.
机译:本文介绍了研究人工神经网络(ANNS)的可能性的研究结果,以对乳房X XMPOCK图像进行分类癌症的变化。 今天的计算机辅助检测(CAD)系统无法检测到100%的病理变化。 ANN的属性之一是广义信息 - 可以识别不仅可以学习的数据,还可以识别与训练集类似的数据。 CAD和ANN的组合可以提供更好的结果,帮助放射科医师采取正确的决定。

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