基于小波神经网络的医学图像分类方法

为了提高乳腺癌早期诊断的准确率，将小波理论与神经网络理论相结合提出改进的小波神经网络算法。将经过预处理的医学图像提取特征值，然后利用基于改进的小波神经网络算法的分类器对医学图像进行分类。通过实验表明此分类器具有较高的分类精度，是有效和可行的；与单独使用后向传播神经网络算法相比分类效果也得到了改善。

Medical image classification based on wavelet neural network

To improve early diagnosis accuracy of breast cancer, an improved wavelet neural network algorithm combining wavelet theory with neural network theory was proposed. It extracted eigenvalues from pretreated medical images, and then classified medical images by using classifier based on improved wavelet neural network algorithm. The experimental results show that the classifier has higher accuracy and the classification is effective and feasible. Compared with neural network algorithm using back-propagating alone, it improves classification results.