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2006 IEEE International Conference on Multimedia and Expo
Automatic Medical Image Annotation and Retrieval using SEMI-SECC
Toronto, ON, Canada
July 09-July 12
ISBN: 1-4244-0366-7
ASCII Text
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Jian Yao, Zhongfei Zhang, Sameer Antani, Rodney Long, George Thoma, "Automatic Medical Image Annotation and Retrieval using SEMI-SECC," Multimedia and Expo, IEEE International Conference on, pp. 2005-2008, 2006 IEEE International Conference on Multimedia and Expo, 2006.
 
 
BibTex
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@article{ 10.1109/ICME.2006.262606,
author = {Jian Yao and Zhongfei Zhang and Sameer Antani and Rodney Long and George Thoma},
title = {Automatic Medical Image Annotation and Retrieval using SEMI-SECC},
journal ={Multimedia and Expo, IEEE International Conference on},
volume = {0},
year = {2006},
isbn = {1-4244-0366-7},
pages = {2005-2008},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICME.2006.262606},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Multimedia and Expo, IEEE International Conference on
TI - Automatic Medical Image Annotation and Retrieval using SEMI-SECC
SN - 1-4244-0366-7
SP2005
EP2008
A1 - Jian Yao,
A1 - Zhongfei Zhang,
A1 - Sameer Antani,
A1 - Rodney Long,
A1 - George Thoma,
PY - 2006
KW - null
VL - 0
JA - Multimedia and Expo, IEEE International Conference on
ER -
 
Jian Yao, Department of Computer Science, State University of New York at Binghamton, Binghamton, NY 13902
Zhongfei Zhang, Department of Computer Science, State University of New York at Binghamton, Binghamton, NY 13902
Sameer Antani, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
Rodney Long, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
George Thoma, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image retrieval method based on SEMI-supervised Semantic Error-Correcting output Codes (SEMI-SEC). The experimental results on IMAGECLEF 2005 [1] annotation data set clearly show the strength and the promise of the presented methods.
Citation:
Jian Yao, Zhongfei Zhang, Sameer Antani, Rodney Long, George Thoma, "Automatic Medical Image Annotation and Retrieval using SEMI-SECC," icme, pp.2005-2008, 2006 IEEE International Conference on Multimedia and Expo, 2006
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