神经网络算法在医学图像压缩中的应用研究.docVIP

神经网络算法在医学图像压缩中的应用研究 摘 要随着图像处理技术的不断进步和发展，数字成像技术在医学中的应用日益广泛，产生了大量的数据，给图像的存储和传输技术提出了严峻的挑战，解决它的关键技术之一就是医学图像压缩技术。 传统的图像压缩方法很多，但大多存在压缩比低、误差大的缺点。基于神经网络的图像压缩技术，在理论和技术上开辟了图像压缩的新途径。BP（Back Propagation）网络是1986年由Rumelhart和McCelland为首的科学家小组提出，是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。BP神经网络算法具有以下优点：网络实质上实现了一个从输入到输出的映射功能、网络能通过学习带正确答案的实例集自动提取“合理的”求解规则、网络具有一定的推广能力。 BP神经网络是一种由输入空间到输出空间的数学映射，能以任意精度逼近任何线性或非线性映射。基于人工神经网络的图像压缩理论与方法成为当今图像处理领域的研究热点。 【关键词】医学图像压缩；误差逆传播算法；BP神经网络；数学映射；自学习； The Application Of Neural Network Algorithm In Medical Image Compression ABSTRACT Along with the advance of image processing technology and development of digital imaging technology has been used increasingly in medical, produced a large amount of data, for image storage and transmission technology put forward the severe challenge, it is one of the key technology of medical image compression technology. The traditional image compression method are many, but most of the low compression ratio, the error big shortcoming. Image compression technology based on neural network, on the theory and technology has opened up a new way of image compression. BP (Back Propagation) network is a group of scientists headed by Rumelhart and McCelland in 1986, is a kind of according to the error Back Propagation algorithm training of the multilayer feedforward network, is currently one of the most widely used neural network model. BP network can learn and store a lot of input - output model mapping, without prior reveal describe the mathematical equations of the mapping relationship. Its learning rule is to use the steepest descent method, by back propagation to constantly adjust the network weights and threshold, minimize the error sum of squares of the network. BP neural network model of topological structures include input layer (input), the hidden layer (hide layer) and out