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1995 International Conference on Image Processing (ICIP'95) - Volume 2
Application of the cluster approximation for the simultaneous restoration and segmentation of tomographic images
Washington D.C.
October 23-October 26
ISBN: 0-8186-7310-9
ASCII Text
x 
 
Chi-hsin Wu, P.C. Doerschuk, "Application of the cluster approximation for the simultaneous restoration and segmentation of tomographic images," Image Processing, International Conference on, vol. 2, pp. 2449, 1995 International Conference on Image Processing (ICIP'95) - Volume 2, 1995.
 
 
BibTex
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@article{ 10.1109/ICIP.1995.537512,
author = {Chi-hsin Wu and P.C. Doerschuk},
title = {Application of the cluster approximation for the simultaneous restoration and segmentation of tomographic images},
journal ={Image Processing, International Conference on},
volume = {2},
year = {1995},
isbn = {0-8186-7310-9},
pages = {2449},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICIP.1995.537512},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Image Processing, International Conference on
TI - Application of the cluster approximation for the simultaneous restoration and segmentation of tomographic images
SN - 0-8186-7310-9
SP
EP
A1 - Chi-hsin Wu,
A1 - P.C. Doerschuk,
PY - 1995
KW - computerised tomography; medical image processing; image restoration; image segmentation; Markov processes; random processes; Bayes methods; edge detection; approximation theory; cluster approximation; tomographic images; image restoration; image segmentation; Bayesian restoration algorithm; Bayesian segmentation algorithm; pixel-line Markov random field; approximation; interactions locality; medical tomography
VL - 2
JA - Image Processing, International Conference on
ER -
 
Chi-hsin Wu, Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
P.C. Doerschuk, Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
We describe a Bayesian restoration and segmentation algorithm based on a pixel-line Markov random field and using an efficient approximation based on locality of interactions. A medical tomography example is given.
Index Terms:
computerised tomography; medical image processing; image restoration; image segmentation; Markov processes; random processes; Bayes methods; edge detection; approximation theory; cluster approximation; tomographic images; image restoration; image segmentation; Bayesian restoration algorithm; Bayesian segmentation algorithm; pixel-line Markov random field; approximation; interactions locality; medical tomography
Citation:
Chi-hsin Wu, P.C. Doerschuk, "Application of the cluster approximation for the simultaneous restoration and segmentation of tomographic images," icip, vol. 2, pp.2449, 1995 International Conference on Image Processing (ICIP'95) - Volume 2, 1995
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