In this article, we describe the used technologies and experimental results for the medical retrieval task at ImageCLEF 2005. The topics of competition this year contain both semantic queries and visual queries. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish the mission. The experimental results show that the text-based approach has higher precision rate than content-based approach. Further, the results of combining both the content-based and text-based approaches are better than those using only one of the approaches. We summarize that the consideration on the image of visual queries can provide more human semantic perception and improve the efficiency for medical image retrieval.
['Pei-Cheng Cheng', 'Been-Chian Chien', 'Hao-Ren Ke', 'Wei-Pang Yang']
NCTU_DBLAB@ImageCLEFmed 2005: Medical Image Retrieval Task.