A Similarity Retrieval Method in Brain Image Sequence Database

Authors:
Haiwei Pan;Qilong Han;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 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:
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Year:
2007

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Abstract

Image mining is more than just an extension of data mining to image domain but an interdisciplinary endeavor. Very few people have systematically investigated this field. Similarity Retrieval in medical image sequence database is an important part in domain-specific application because there are several technical aspects which make this problem challenging. 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 the similarity for two medical images is not important, but rather, 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 the possible Space-Occupying Lesion (PSO) in brain images and ISSP for similarity retrieval. Our experiments demonstrate that the results of similarity retrieval are meaningful and interesting to medical doctors.