Mining image sequence similarity patterns in brain images

Authors:
Pan Haiwei;Xiaoqin Xie;Zhang Wei;Jianzhong Li
Affiliations:
Dept. of Computer Science, Harbin Engineering University, Harbin, P.R. China;Dept. of Computer Science, Harbin Engineering University, Harbin, P.R. China;Dept. of Computer Science, Harbin Institute of Technology, Harbin, P.R. China;Dept. of Computer Science, Harbin Institute of Technology, Harbin, P.R. China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

The high incidence of brain disease, especially brain tumor, has increased significantly in recent years. It is becoming more and more concernful to discover knowledge through mining medical brain image to aid doctors' diagnosis. In this paper, we introduce a notion of image sequence similarity patterns (ISSP) for medical image database. These patterns are significant in medical images because it is the similarity of objects each of which has an image sequence that is meaningful. We design the new algorithms with the guidance of the domain knowledge to discover ISSP for similarity retrieval. Our experiments demonstrate that the results of similarity retrieval are satisfying.