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16th International Conference on Pattern Recognition (ICPR'02) - Volume 1
Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
ASCII Text
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Hotaka Takizawa, Shinji Yamamoto, Tohru Matsumoto, Yukio Tateno, Takeshi Iinuma, Mitsuomi Matsumoto, "Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models," Pattern Recognition, International Conference on, vol. 1, pp. 10099, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002.
 
 
BibTex
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@article{ 10.1109/ICPR.2002.1044622,
author = {Hotaka Takizawa and Shinji Yamamoto and Tohru Matsumoto and Yukio Tateno and Takeshi Iinuma and Mitsuomi Matsumoto},
title = {Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models},
journal ={Pattern Recognition, International Conference on},
volume = {1},
year = {2002},
issn = {1051-4651},
pages = {10099},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044622},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models
SN - 1051-4651
SP
EP
A1 - Hotaka Takizawa,
A1 - Shinji Yamamoto,
A1 - Tohru Matsumoto,
A1 - Yukio Tateno,
A1 - Takeshi Iinuma,
A1 - Mitsuomi Matsumoto,
PY - 2002
KW - null
VL - 1
JA - Pattern Recognition, International Conference on
ER -
 
Hotaka Takizawa, Toyohashi University of Technology
Shinji Yamamoto, Toyohashi University of Technology
Tohru Matsumoto, National Institute of Radiological Science
Yukio Tateno, National Institute of Radiological Science
Takeshi Iinuma, National Institute of Radiological Science
Mitsuomi Matsumoto, Tokyo Metropolitan University of Health Sciences
In this paper, we propose a new recognition method of lung nodules from X-ray CT images using 3D Markov random field(MRF) models. Pathological shadow candidates are detected by a mathematical morphology filter, and volume of interest(VOI) areas which include the shadow candidates are extracted. The probabilities of the hypotheses that the VOI areas come from nodules(which are candidates of cancers) and blood vessels are calculated using nodule and blood vessel models evaluating the relations between these object models by 3D MRF models. If the probabilities for the nodule models are higher, the shadow candidates are determined to be abnormal. By applying this new recognition method to actual 38 CT images, good results has been acquired.
Citation:
Hotaka Takizawa, Shinji Yamamoto, Tohru Matsumoto, Yukio Tateno, Takeshi Iinuma, Mitsuomi Matsumoto, "Recognition of Lung Nodules from X-ray CT Images Using 3D Markov Random Field Models," icpr, vol. 1, pp.10099, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002
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