This paper presents a content-based medical image retrieval (CBIR) method that used in medical CT images of liver lesions with a computer-assisted diagnosis. According to medical CT images characteristics of blurred boundaries and the unconspicuous region, the liver region of interest is extracted by using semi-automatic method. We extract local co-occurrence matrix texture features and intensity features, and use improved non-tensor product wavelet filter to extract the image global features. Experimental results show that this method can improve the detection rate of lesions. It obtains good results in hepatic hemangioma and HCC which are difficult differential diagnosis both of rich blood supply to tumors.
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