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Volumn 11, Issue 1, 2012, Pages

Three-dimensional multiphase segmentation of X-ray CT data of porous materials using a Bayesian Markov random field framework

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED OPERATIONS; CONTAMINANT REMEDIATION; CT TECHNOLOGY; DATA SETS; DUAL-ENERGY; ENHANCED OIL RECOVERY; FLUID DYNAMICS SIMULATIONS; GLASS BEAD; GRAY SCALE; IMAGE ALIGNMENT; IMAGE MODELS; INTERFACIAL DYNAMICS; LARGE DATASETS; MARKOV RANDOM FIELD; MARKOV RANDOM FIELDS; MICRO-SCALES; NON-INVASIVE IMAGING; PARTIALLY SATURATED; SEGMENTATION METHODS; SEGMENTATION RESULTS; SYNCHROTRON X RAYS; THEORETICAL ASPECTS; X-RAY COMPUTED TOMOGRAPHY; X-RAY CT; X-RAY MICRO-CT;

EID: 84858272544     PISSN: None     EISSN: 15391663     Source Type: Journal    
DOI: 10.2136/vzj2011.0082     Document Type: Article
Times cited : (39)

References (41)
  • 1
    • 77953578609 scopus 로고    scopus 로고
    • Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data
    • doi:10.1016/j.geoderma.2010.03.015
    • Baveye, P.C., M. Laba, W. Otten, L. Bouckaert, P. Dello Sterpaio, R.R. Goswami, et al. 2010. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data. Geoderma 157:51-63. doi:10.1016/j.geoderma.2010.03.015
    • (2010) Geoderma , vol.157 , pp. 51-63
    • Baveye, P.C.1    Laba, M.2    Otten, W.3    Bouckaert, L.4    Dello Sterpaio, P.5    Goswami, R.R.6
  • 2
    • 0030148684 scopus 로고    scopus 로고
    • Bayesian image classifi-cation using Markov random fields
    • doi:10.1016/0262-8856(95)01072-6
    • Berthod, M., Z. Kato, S. Yu, and J. Zerubia. 1996. Bayesian image classifi-cation using Markov random fields. Image Vis. Comput. 14:285-295. doi:10.1016/0262-8856(95)01072-6
    • (1996) Image Vis. Comput. , vol.14 , pp. 285-295
    • Berthod, M.1    Kato, Z.2    Yu, S.3    Zerubia, J.4
  • 3
    • 0000913755 scopus 로고
    • Spatial interaction and the statistical analysis of lattice systems
    • Besag, J.E. 1974. Spatial interaction and the statistical analysis of lattice systems. J. R. Stat. Soc. B 36:192-236.
    • (1974) J. R. Stat. Soc. B , vol.36 , pp. 192-236
    • Besag, J.E.1
  • 4
    • 0000013152 scopus 로고
    • On the statistical analysis of dirty pictures
    • Besag, J.E. 1986. On the statistical analysis of dirty pictures. J. R. Stat. Soc. B 48:259-302.
    • (1986) J. R. Stat. Soc. B , vol.48 , pp. 259-302
    • Besag, J.E.1
  • 5
    • 0344236266 scopus 로고    scopus 로고
    • Metaheuristics in combinatorial optimization: Overview and conceptual comparison
    • doi:10.1145/937503.937505
    • Blum, C., and A. Roli. 2003. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. Surv. 35:268-308. doi:10.1145/937503.937505
    • (2003) ACM Comput. Surv. , vol.35 , pp. 268-308
    • Blum, C.1    Roli, A.2
  • 7
    • 76849086040 scopus 로고    scopus 로고
    • Variational Bayesian Image restoration with a product of spatially weighted total varia-tion image priors
    • doi:10.1109/TIP.2009.2033398
    • Chantas, G., N.P. Galatsanos, R. Molina, and A.K. Katsaggelos. 2010. Variational Bayesian Image restoration with a product of spatially weighted total varia-tion image priors. IEEE Trans. Image Process. 19:351-362. doi:10.1109/TIP.2009.2033398
    • (2010) IEEE Trans. Image Process , vol.19 , pp. 351-362
    • Chantas, G.1    Galatsanos, N.P.2    Molina, R.3    Katsaggelos, A.K.4
  • 8
    • 31544461548 scopus 로고    scopus 로고
    • Fuzzy c-means clustering with spatial information for image segmentation
    • doi:10.1016/j.compmedimag.2005.10.001
    • Chuang, K.-S., H.-L. Tzeng, S. Chen, J. Wu, and T.-J. Chen. 2006. Fuzzy c-means clustering with spatial information for image segmentation. Comput. Med. Imaging Graph. 30:9-15. doi:10.1016/j.compmedimag.2005.10.001
    • (2006) Comput. Med. Imaging Graph. , vol.30 , pp. 9-15
    • Chuang, K.-S.1    Tzeng, H.-L.2    Chen, S.3    Wu, J.4    Chen, T.-J.5
  • 9
    • 14644412825 scopus 로고    scopus 로고
    • Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field model
    • Deng, H., and D.A. Clausi. 2005. Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field model. IEEE Trans. Geosci. Remote Sens. 43:528-538.
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , pp. 528-538
    • Deng, H.1    Clausi, D.A.2
  • 10
    • 0021517736 scopus 로고
    • Bayes smoothing algorithms for segmentation of binary images modeled by Markov random fields
    • Derin, H., H. Elliott, R. Cristi, and D. Geman. 1984. Bayes smoothing algorithms for segmentation of binary images modeled by Markov random fields. IEEE Trans. Pattern Anal. Mach. Intell. 6:707-720.
    • (1984) IEEE Trans. Pattern Anal. Mach. Intell. , vol.6 , pp. 707-720
    • Derin, H.1    Elliott, H.2    Cristi, R.3    Geman, D.4
  • 11
    • 35348974662 scopus 로고    scopus 로고
    • A comparison of 2D vs. 3D thresholding of X-ray CT imagery
    • doi:10.4141/CJSS06017
    • Elliot, T.R., and R.J. Heck. 2007. A comparison of 2D vs. 3D thresholding of X-ray CT imagery. Can. J. Soil Sci. 87:405-412. doi:10.4141/CJSS06017
    • (2007) Can. J. Soil Sci. , vol.87 , pp. 405-412
    • Elliot, T.R.1    Heck, R.J.2
  • 12
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images
    • doi:10.1109/TPAMI.1984.4767596
    • Geman, S., and D. Geman. 1984. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Mach. Intell. 6:721-741. doi:10.1109/TPAMI.1984.4767596
    • (1984) IEEE Trans. Pattern Anal. Mach. Intell. , vol.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 17
    • 72149119740 scopus 로고    scopus 로고
    • Segmentation of X-ray CT images of porous materials: A crucial step for characterization and quantitative analysis of pore structures
    • doi:10.1029/2009WR008087
    • Iassonov, P., T. Gebrenegus, and M. Tuller. 2009. Segmentation of X-ray CT images of porous materials: A crucial step for characterization and quantitative analysis of pore structures. Water Resour. Res. 45:W09415. doi:10.1029/2009WR008087
    • (2009) Water Resour. Res. , vol.45
    • Iassonov, P.1    Gebrenegus, T.2    Tuller, M.3
  • 18
    • 77349095023 scopus 로고    scopus 로고
    • Application of image segmentation for correc tion of intensity bias in X-ray CT images
    • doi:10.2136/vzj2009.0042
    • Iassonov, P., and M. Tuller. 2010. Application of image segmentation for correc tion of intensity bias in X-ray CT images. Vadose Zone J. 9:187-191. doi:10.2136/vzj2009.0042
    • (2010) Vadose Zone J , vol.9 , pp. 187-191
    • Iassonov, P.1    Tuller, M.2
  • 20
    • 50149110399 scopus 로고    scopus 로고
    • Imaging and image processing in porous media research
    • doi:10.1016/j.advwatres.2008.01.022
    • Kaestner, A., E. Lehmann, and M. Stampanoni. 2008. Imaging and image processing in porous media research. Adv. Water Resour. 31:1174-1187. doi:10.1016/j.advwatres.2008.01.022
    • (2008) Adv. Water Resour. , vol.31 , pp. 1174-1187
    • Kaestner, A.1    Lehmann, E.2    Stampanoni, M.3
  • 21
    • 0036877268 scopus 로고    scopus 로고
    • An object-oriented random-number package with many long streams and substreams
    • doi:10.1287/opre.50.6.1073.358
    • L'Ecuyer, P., R. Simard, E.J. Chen, and W.D. Kelton. 2002. An object-oriented random-number package with many long streams and substreams. Oper. Res. 50:1073-1075. doi:10.1287/opre.50.6.1073.358
    • (2002) Oper. Res. , vol.50 , pp. 1073-1075
    • L'Ecuyer, P.1    Simard, R.2    Chen, E.J.3    Kelton, W.D.4
  • 22
    • 77956058909 scopus 로고    scopus 로고
    • A novel MAP-MRF approach for multispectral image contextual classification using combina-tion of suboptimal iterative algorithms
    • doi:10.1016/j.patrec.2010.04.007
    • Levada, A.L.M., N.D.A. Mascarenhas, and A. Tannus. 2010. A novel MAP-MRF approach for multispectral image contextual classification using combina-tion of suboptimal iterative algorithms. Pattern Recognit. Lett. 31:1795-1808. doi:10.1016/j.patrec.2010.04.007
    • (2010) Pattern Recognit. Lett. , vol.31 , pp. 1795-1808
    • Levada, A.L.M.1    Mascarenhas, N.D.A.2    Tannus, A.3
  • 26
    • 0003970661 scopus 로고
    • Markov random fields and their applica-tions, Providence, RI
    • Kindermann, R., and J.L. Snell. 1980. Markov random fields and their applica-tions. Am. Math. Soc., Providence, RI.
    • (1980) Am. Math. Soc.
    • Kindermann, R.1    Snell, J.L.2
  • 27
    • 26444479778 scopus 로고
    • Optimization by simulated annealing
    • Kirkpatrick, S., C.D. Gelatt, and M.P. Vecchi. 1983. Optimization by simulated annealing. Science 220:671-680.
    • (1983) Science , vol.220 , pp. 671-680
    • Kirkpatrick, S.1    Gelatt, C.D.2    Vecchi, M.P.3
  • 29
    • 34250415938 scopus 로고
    • Gibbs and Markov random systems with constraints
    • doi:10.1007/BF01011714
    • Moussouris, J. 1974. Gibbs and Markov random systems with constraints. J. Stat. Phys. 10:11-33. doi:10.1007/BF01011714
    • (1974) J. Stat. Phys. , vol.10 , pp. 11-33
    • Moussouris, J.1
  • 30
    • 42149168865 scopus 로고    scopus 로고
    • NVIDIA CUDA: Compute Unified Device Architecture programming guide
    • NVIDIA Corp, version 1.1, Santa Clara, CA
    • NVIDIA Corp. 2007. NVIDIA CUDA: Compute Unified Device Architecture programming guide, version 1.1. Tech. Rep. NVIDIA Corp., Santa Clara, CA.
    • (2007) Tech. Rep. NVIDIA Corp
  • 31
  • 32
    • 77952876579 scopus 로고    scopus 로고
    • Image analysis algorithms for estimating porous media multiphase flow variables from computed microtomography data: A validation study
    • doi:10.1007/s10596-009-9130-5
    • Porter, M.L., and D. Wildenschild. 2010. Image analysis algorithms for estimating porous media multiphase flow variables from computed microtomography data: A validation study. Comput. Geosci. 14:15-30. doi:10.1007/s10596-009-9130-5
    • (2010) Comput. Geosci. , vol.14 , pp. 15-30
    • Porter, M.L.1    Wildenschild, D.2
  • 33
    • 77955563008 scopus 로고    scopus 로고
    • Measurement and prediction of the relationship between capillary pressure, saturation, and interfacial area in a NAPL-water-glass bead system
    • doi:10.1029/2009WR007786
    • Porter, M.L., D. Wildenschild, G. Grant, and J.I. Gerhard. 2010. Measurement and prediction of the relationship between capillary pressure, saturation, and interfacial area in a NAPL-water-glass bead system. Water Resour. Res. 46:W08512. doi:10.1029/2009WR007786
    • (2010) Water Resour. Res. , vol.46
    • Porter, M.L.1    Wildenschild, D.2    Grant, G.3    Gerhard, J.I.4
  • 34
    • 84858245817 scopus 로고    scopus 로고
    • Available at, verified 4 Dec. 2011, Univ. of Chicago, Chicago
    • Rivers, M.L. 2010. GSECARS tomography processing software. Available at cars9.uchicago.edu/software/idl/tomography.html (verified 4 Dec. 2011). Univ. of Chicago, Chicago.
    • (2010) GSECARS Tomography Processing Software
    • Rivers, M.L.1
  • 35
    • 77956784233 scopus 로고    scopus 로고
    • Segmentation of X-ray microtomography images of soil using gradient masks
    • doi:10.1016/j.cageo.2010.02.007
    • Schlüter, S., U. Weller, and H.-J. Vogel. 2010. Segmentation of X-ray microtomography images of soil using gradient masks. Comput. Geosci. 36:1246-1251. doi:10.1016/j.cageo.2010.02.007
    • (2010) Comput. Geosci. , vol.36 , pp. 1246-1251
    • Schlüter, S.1    Weller, U.2    Vogel, H.-J.3
  • 36
    • 85032751582 scopus 로고    scopus 로고
    • Signal and image processing with belief propagation
    • doi:10.1109/MSP.2007.914235
    • Sudderth, E.B., and W.T. Freeman. 2008. Signal and image processing with belief propagation. IEEE Signal Process. Mag. 25:114-121. doi:10.1109/MSP.2007.914235.
    • (2008) IEEE Signal Process. Mag. , vol.25 , pp. 114-121
    • Sudderth, E.B.1    Freeman, W.T.2
  • 37
    • 83055169047 scopus 로고    scopus 로고
    • Evaluation of an advanced benchtop micro-computed tomography system for quantifying porosities and pore-size distributions of two Brazilian Oxisols
    • doi:10.2136/sssaj2010.0245
    • Vaz, C.M.P., I.C. de Maria, P.O. Lasso, and M. Tuller. 2011. Evaluation of an advanced benchtop micro-computed tomography system for quantifying porosities and pore-size distributions of two Brazilian Oxisols. Soil Sci. Soc. Am. J. 75:832-841. doi:10.2136/sssaj2010.0245
    • (2011) Soil Sci. Soc. Am. J. , vol.75 , pp. 832-841
    • Vaz, C.M.P.1    de Maria, I.C.2    Lasso, P.O.3    Tuller, M.4
  • 38
    • 79955478652 scopus 로고    scopus 로고
    • Comparison of image segmentation methods in simulated 2D and 3D microtomographic images of soil aggregates
    • doi:10.1016/j.geoderma.2011.01.006
    • Wang, W., A.N. Kravchenko, A.J.M. Smucker, and M.L. Rivers. 2011. Comparison of image segmentation methods in simulated 2D and 3D microtomographic images of soil aggregates. Geoderma 162:231-241. doi:10.1016/j.geoderma.2011.01.006
    • (2011) Geoderma , vol.162 , pp. 231-241
    • Wang, W.1    Kravchenko, A.N.2    Smucker, A.J.M.3    Rivers, M.L.4
  • 39
    • 24644495883 scopus 로고    scopus 로고
    • Quantitative analysis of flow processes in a sand using synchrotron-based X-ray microtomography
    • doi:10.2113/4.1.112
    • Wildenschild, D., J.W. Hopmans, M.L. Rivers, and A.J.R. Kent. 2005. Quantitative analysis of flow processes in a sand using synchrotron-based X-ray microtomography. Vadose Zone J. 4:112-126. doi:10.2113/4.1.112
    • (2005) Vadose Zone J , vol.4 , pp. 112-126
    • Wildenschild, D.1    Hopmans, J.W.2    Rivers, M.L.3    Kent, A.J.R.4
  • 40
    • 0037108577 scopus 로고    scopus 로고
    • Using X-ray computed microtomography in hydrology: Systems, resolutions and limitations
    • doi:10.1016/S0022-1694(02)00157-9
    • Wildenschild, D., J.W. Hopmans, C.M.P. Vaz, M.L. Rivers, D. Rikard, and B.S.B. Christensen. 2002. Using X-ray computed microtomography in hydrology: Systems, resolutions and limitations. J. Hydrol. 267:285-297. doi:10.1016/S0022-1694(02)00157-9
    • (2002) J. Hydrol. , vol.267 , pp. 285-297
    • Wildenschild, D.1    Hopmans, J.W.2    Vaz, C.M.P.3    Rivers, M.L.4    Rikard, D.5    Christensen, B.S.B.6
  • 41
    • 0029267620 scopus 로고
    • Combinatorial optimization with use of guided evolutionary simulated annealing
    • doi:10.1109/72.363466
    • Yip, P.P.C., and Y.-H. Pao. 1995. Combinatorial optimization with use of guided evolutionary simulated annealing. IEEE Trans. Neural Netw. 6:290-295. doi:10.1109/72.363466
    • (1995) IEEE Trans. Neural Netw. , vol.6 , pp. 290-295
    • Yip, P.P.C.1    Pao, Y.-H.2


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