关键词: 主元分析, 图像检索, 特征提取, 医学图像

Abstract: The results of medical image retrieval mainly depend on the quality of feature extraction.For the characteristics of the medical image，three typical feature extraction methods such as histograms，Gabor wavelet and invariant matrix are adopted to extract color feature，texture feature and shape feature respectively.But those features extracted by the various methods are used to medical image retrieval directly，the results are not satisfactory.So a feature-level data fusion algorithm based on PCA is proposed，the influence of classification caused by the wide gap of the value in different features can be avoided，in the mean time，it can reduce the dimension and the redundancy of the features.The experiments proves that the fused features can express the content of the medical image better，and a better result can be gotten in the medical image retrieval.

Key words: Principle Component Analysis（PCA）, image retrieval, feature extraction, medical image