Abstract
This paper aims at finding images that are similar to a medical image example query. We propose several image features based on wavelet coefficients, including color histogram, gray-spatial histogram, coherence moment, and gray correlogram, to facilitate the retrieval of similar medical images. The initial retrieval results are obtained via visual feature analysis. An automatic feedback mechanism that clusters visually and textually similar images among these initial results was also proposed to help refine the query. In the ImageCLEF 2004 evaluation, the experimental results show that our system is excellence in mean average precision.
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Cheng, PC., Chien, BC., Ke, HR., Yang, WP. (2005). SMIRE: Similar Medical Image Retrieval Engine. In: Peters, C., Clough, P., Gonzalo, J., Jones, G.J.F., Kluck, M., Magnini, B. (eds) Multilingual Information Access for Text, Speech and Images. CLEF 2004. Lecture Notes in Computer Science, vol 3491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11519645_73
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DOI: https://doi.org/10.1007/11519645_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27420-9
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