SMIRE: Similar medical image retrieval engine

Pei Cheng Cheng; Been Chian Chien; Hao Ren Ke; Wei Pang Yang

doi:10.1007/11519645_73

SMIRE: Similar medical image retrieval engine

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

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

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 language	English
Pages (from-to)	750-760
Number of pages	11
Journal	Lecture Notes in Computer Science
Volume	3491
DOIs	https://doi.org/10.1007/11519645_73
Publication status	Published - 2005
Externally published	Yes
Event	5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images - Bath, United Kingdom Duration: 2004 Sept 15 → 2004 Sept 17

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/11519645_73

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@article{c16002e9315642fcbae7de2f472f23be,

title = "SMIRE: Similar medical image retrieval engine",

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.",

author = "Cheng, {Pei Cheng} and Chien, {Been Chian} and Ke, {Hao Ren} and Yang, {Wei Pang}",

year = "2005",

doi = "10.1007/11519645_73",

language = "English",

volume = "3491",

pages = "750--760",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

publisher = "Springer Science and Business Media Deutschland GmbH",

note = "5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images ; Conference date: 15-09-2004 Through 17-09-2004",

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T2 - 5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images

AU - Cheng, Pei Cheng

AU - Chien, Been Chian

AU - Ke, Hao Ren

AU - Yang, Wei Pang

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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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EP - 760

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

Y2 - 15 September 2004 through 17 September 2004

ER -

SMIRE: Similar medical image retrieval engine

Abstract

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