Medical image retrieval based on wavelet texture, semantic feature and relevance feedback
BA Te-er · Journal of Circuits and Systems · 2007
We propose a medical image retrieval method based on the combination of wavelet texture, semantic feature and relevance feedback for two kinds of medical image databases, which are sternums and chest CT images. First, we analyze three methods of texture descriptor: wavelet transform, texture spectrum and gray level co-occurrence matrix, and utilize the method of medical image retrieval by wavelet transform. In order to improve the retrieval accuracies, semantic feature is combined with wavelet transform. Then the technique of relevance feedback is used in the algorithm to enhance the effectiveness of retrieval. Finally, a simple prototype system is developed to compare the precision, the recall rate and the average serial number by three experiments. Experimental results show that the proposed approach is effective.