关键词: 医学图像, 不变矩, 矢量标准化, 神经网络, 模式识别, 模糊分类

Abstract: A medical image recognition method based on moment invariant feature and neural networks is proposed, including the moment invariant feature extraction, moment invariant vector standardization, fuzzy preprocessing, BP net and competition selection. The feature vector of medical images, as extracted by the method of moment invariant, can effectively recognize the images characterized by translation, rotation and scaling invariants. Utilizing neural networks for classification, the extracted feature vector is classified. By use of fuzzy method, the feature data-input is preprocessed then recognized. Thus, the attribution of each and every image pattern is supposed to be expressed by a number from 0 to 1 to indicate how an image pattern is attributed to a class/sort. Experiment results demonstrated that the method is effective, and the net possesses high classing ability if trained up.