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Sternum Image Retrieval Based on High-level Semantic Information and Low-level Features

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2 Author(s)
Qin Chen ; Inst. of Inf. Sci. & Eng., Ningbo Univ., Ningbo ; Xiaoying Tai

In allusion to sternum images, herein we describe a system which supports image retrieval by content. Attention is focused on high-level semantic information representation of medical images. Then a feature fusion algorithm of medical image retrieval using high-level semantic information combining low-level features is presented. A prototype system which supports query by example is designed and implemented on vista operating system, using VC++ and Access. The performance of the method is illustrated using examples from an image database composed of 134 medical images, and the comparison of the retrieval results shows that the approach proposed in this paper is effective.

Published in:

BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on  (Volume:1 )

Date of Conference:

27-30 May 2008