SMIRE: Similar medical image retrieval engine

Pei Cheng Cheng, Been Chian Chien, Hao-Ren Ke, Wei Pang Yang

Research output: Contribution to journalConference article

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.

Original languageEnglish
Pages (from-to)750-760
Number of pages11
JournalLecture Notes in Computer Science
Volume3491
Publication statusPublished - 2005 Sep 26
Event5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images - Bath, United Kingdom
Duration: 2004 Sep 152004 Sep 17

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Cheng, P. C., Chien, B. C., Ke, H-R., & Yang, W. P. (2005). SMIRE: Similar medical image retrieval engine. Lecture Notes in Computer Science, 3491, 750-760.