메뉴 건너뛰기




Volumn 13, Issue 7, 2012, Pages 520-533

Brain tissue segmentation based on spatial information fusion by Dempster-Shafer theory

Author keywords

Dempster Shafer theory (DST); Fuzzy c mean (FCM); Magnetic resonance imaging (MRI); Segmentation

Indexed keywords

ACCURACY INDEX; AUTOMATIC SEGMENTATIONS; BELIEF STRUCTURES; BRAIN MRI; BRAIN TISSUE; DEMPSTER-SHAFER THEORY; FUZZY C MEAN; NONUNIFORMITY; QUANTITATIVE COMPARISON; SPATIAL INFORMATIONS;

EID: 84864584104     PISSN: 18691951     EISSN: 1869196X     Source Type: Journal    
DOI: 10.1631/jzus.C1100288     Document Type: Article
Times cited : (14)

References (46)
  • 1
    • 5544252933 scopus 로고    scopus 로고
    • A fuzzystatistical contour model for MRI segmentation and target tracking
    • doi:10.1117/12.541406
    • Abd-Almageed, W., El-Osery, A., Smith, C., 2004. A fuzzystatistical contour model for MRI segmentation and target tracking. SPIE, 5438:25-33. doi:10.1117/12.541406
    • (2004) SPIE , vol.5438 , pp. 25-33
    • Abd-Almageed, W.1    El-Osery, A.2    Smith, C.3
  • 2
    • 78650387485 scopus 로고    scopus 로고
    • A new approach for speech enhancement based on singular value decomposition and wavelet transform
    • Afzalian, A., Karami Mollaei, M.R., Dousti, M., Ghasemi, J., 2010. A new approach for speech enhancement based on singular value decomposition and wavelet transform. Aust. J. Basic Appl. Sci., 4(8):3602-3612.
    • (2010) Aust. J. Basic Appl. Sci. , vol.4 , Issue.8 , pp. 3602-3612
    • Afzalian, A.1    Karami Mollaei, M.R.2    Dousti, M.3    Ghasemi, J.4
  • 3
    • 0036489378 scopus 로고    scopus 로고
    • A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data
    • doi:10.1109/42. 996338
    • Ahmed, M.N., Yamany, S.M., Mohamed, N., Farag, A.A., Moriarty, T., 2002. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans. Med. Imag., 21(3):193-199. doi:10.1109/42. 996338
    • (2002) IEEE Trans. Med. Imag. , vol.21 , Issue.3 , pp. 193-199
    • Ahmed, M.N.1    Yamany, S.M.2    Mohamed, N.3    Farag, A.A.4    Moriarty, T.5
  • 5
    • 0035341151 scopus 로고    scopus 로고
    • An expert system for multi-criteria decision making using Dempster Shafer theory
    • doi:10.1016/S0957-4174(01)00020-3
    • Beynon, M., Cosker, D., Marshall, D., 2001. An expert system for multi-criteria decision making using Dempster Shafer theory. Expert Syst. Appl., 20(4):357-367. doi:10.1016/S0957-4174(01)00020-3
    • (2001) Expert Syst. Appl. , vol.20 , Issue.4 , pp. 357-367
    • Beynon, M.1    Cosker, D.2    Marshall, D.3
  • 7
    • 0032650531 scopus 로고    scopus 로고
    • Fuzzy Dempster-Shafer reasoning for rule-based classifiers
    • doi:10.1002/(SICI)1098-111X(199906)14: 6<559::AID-INT2>3.0.CO;2-#
    • Binaghi, E., Madella, P., 1999. Fuzzy Dempster-Shafer reasoning for rule-based classifiers. Int. J. Intell. Syst., 14(6):559-583. doi:10.1002/(SICI)1098-111X(199906)14: 6<559::AID-INT2>3.0.CO;2-#
    • (1999) Int. J. Intell. Syst. , vol.14 , Issue.6 , pp. 559-583
    • Binaghi, E.1    Madella, P.2
  • 8
    • 0030192238 scopus 로고    scopus 로고
    • Some aspects of Dempster-Shafer evidence theory for classification of multi-modality medical images taking partial volume effect into account
    • doi:10.1016/0167-8655(96) 00039-6
    • Bloch, I., 1996. Some aspects of Dempster-Shafer evidence theory for classification of multi-modality medical images taking partial volume effect into account. Pattern Recogn. Lett., 17(8):905-919. doi:10.1016/0167-8655(96) 00039-6
    • (1996) Pattern Recogn. Lett. , vol.17 , Issue.8 , pp. 905-919
    • Bloch, I.1
  • 9
    • 0025445376 scopus 로고
    • 3-D segmentation of MR images of the head for 3-D display
    • doi:10.1109/42. 56342
    • Bomans, M., Hohne, K.H., Tiede, U., Riemer, M., 1990. 3-D segmentation of MR images of the head for 3-D display. IEEE Trans. Med. Imag., 9(2):177-183. doi:10.1109/42. 56342
    • (1990) IEEE Trans. Med. Imag. , vol.9 , Issue.2 , pp. 177-183
    • Bomans, M.1    Hohne, K.H.2    Tiede, U.3    Riemer, M.4
  • 10
    • 0028069240 scopus 로고
    • Estimation of CSF, white and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images
    • doi:10.1016/0895-6111(94)90058-2
    • Brandt, M.E., Bohan, T.P., Kramer, L.A., Fletcher, J.M., 1994. Estimation of CSF, white and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images. Comput. Med. Imag. Graph., 18(1):25-34. doi:10.1016/0895-6111(94)90058-2
    • (1994) Comput. Med. Imag. Graph. , vol.18 , Issue.1 , pp. 25-34
    • Brandt, M.E.1    Bohan, T.P.2    Kramer, L.A.3    Fletcher, J.M.4
  • 11
    • 84947812228 scopus 로고    scopus 로고
    • Compensation of spatial inhomogeneity in mri based on a multi-valued image model and a parametric bias estimate
    • doi:10.1007/BFb0046948
    • Brechbühler, C., Gerig, G., Székely, G., 1996. Compensation of Spatial Inhomogeneity in MRI Based on a Multi-valued Image Model and a Parametric Bias Estimate. Proc. Visualization in Biomedical Computing, p.141-146. doi:10.1007/BFb0046948
    • (1996) Proc. Visualization in Biomedical Computing , pp. 141-146
    • Brechbühler, C.1    Gerig, G.2    Székely, G.3
  • 12
    • 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., Tzeng, H.L., Chen, S., Wu, J., Chen, T.J., 2006. Fuzzy c-means clustering with spatial information for image segmentation. Comput. Med. Imag. Graph., 30(1): 9-15. doi:10.1016/j.compmedimag.2005.10.001
    • (2006) Comput. Med. Imag. Graph. , vol.30 , Issue.1 , pp. 9-15
    • Chuang, K.S.1    Tzeng, H.L.2    Chen, S.3    Wu, J.4    Chen, T.J.5
  • 13
    • 79151470301 scopus 로고    scopus 로고
    • Combining stationary wavelet transform and self-organizing maps for brain MR image segmentation
    • doi:10.1016/j.engappai.2010.09.008
    • Demirhan, A., Güler, I., 2011. Combining stationary wavelet transform and self-organizing maps for brain MR image segmentation. Eng. Appl. Artif. Intell., 24(2):358-367. doi:10.1016/j.engappai.2010.09.008
    • (2011) Eng. Appl. Artif. Intell. , vol.24 , Issue.2 , pp. 358-367
    • Demirhan, A.1    Güler, I.2
  • 14
    • 80053426543 scopus 로고    scopus 로고
    • A new approach for speech enhancement based on eigenvalue spectral subtraction
    • Ghasemi, J., Karami Mollaei, M.R., 2009. A new approach for speech enhancement based on eigenvalue spectral subtraction. Signal Process. Int. J., 3(4):34-41.
    • (2009) Signal Process. Int. J. , vol.3 , Issue.4 , pp. 34-41
    • Ghasemi, J.1    Karami Mollaei, M.R.2
  • 16
    • 2942517541 scopus 로고    scopus 로고
    • Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error
    • doi:10.1002/hbm.20013
    • Gispert, J.D., Reig, S., Pascau, J., Vaquero, J.J., Garcia-Barreno, P., Desco, M., 2004. Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error. Human Brain Map., 22(2):133-144. doi:10.1002/hbm.20013
    • (2004) Human Brain Map. , vol.22 , Issue.2 , pp. 133-144
    • Gispert, J.D.1    Reig, S.2    Pascau, J.3    Vaquero, J.J.4    Garcia-Barreno, P.5    Desco, M.6
  • 17
    • 27644434677 scopus 로고    scopus 로고
    • Unbiased segmentation of diffusion-weighted magnetic resonance images of the brain using iterative clustering
    • doi:10.1016/j.mri.2005.07.010
    • Hadjiprocopis, A., Rashid, W., Tofts, P.S., 2005. Unbiased segmentation of diffusion-weighted magnetic resonance images of the brain using iterative clustering. Magn. Reson. Imag., 23(8):877-885. doi:10.1016/j.mri.2005.07.010
    • (2005) Magn. Reson. Imag. , vol.23 , Issue.8 , pp. 877-885
    • Hadjiprocopis, A.1    Rashid, W.2    Tofts, P.S.3
  • 18
    • 84864631433 scopus 로고    scopus 로고
    • Multispectral brain mri segmentation based on fuzzy classifiers and evidence theory
    • Hasanzadeh, M., Kasaei, S., 2007. Multispectral Brain MRI Segmentation Based on Fuzzy Classifiers and Evidence Theory. 15th Iranian Conf. on Electrical Engineering, p.1-5.
    • (2007) 15th Iranian Conf. on Electrical Engineering , pp. 1-5
    • Hasanzadeh, M.1    Kasaei, S.2
  • 19
    • 0032126545 scopus 로고    scopus 로고
    • Applicability of semi-automatic segmentation for volumetric analysis of brain lesions
    • doi:10.3109/030919 09809032536
    • Heinonen, T., Dastidar, P., Eskola, H., Frey, H., Ryymin, P., Laasonen, E., 1998. Applicability of semi-automatic segmentation for volumetric analysis of brain lesions. J. Med. Eng. Technol., 22(4):173-178. doi:10.3109/030919 09809032536
    • (1998) J. Med. Eng. Technol. , vol.22 , Issue.4 , pp. 173-178
    • Heinonen, T.1    Dastidar, P.2    Eskola, H.3    Frey, H.4    Ryymin, P.5    Laasonen, E.6
  • 20
    • 0036532868 scopus 로고    scopus 로고
    • An attractable snakes based on the greedy algorithm for contour extraction
    • doi:10.1016/S0031-3203(01)00085-1
    • Ji, L., Yan, H., 2002. An attractable snakes based on the greedy algorithm for contour extraction. Pattern Recogn., 35(4):791-806. doi:10.1016/S0031-3203(01)00085-1
    • (2002) Pattern Recogn. , vol.35 , Issue.4 , pp. 791-806
    • Ji, L.1    Yan, H.2
  • 21
    • 79956352343 scopus 로고    scopus 로고
    • A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image
    • doi:10.1016/j.comp medimag.2010.12.001
    • Ji, Z.X., Sun, Q.S., Xia, D.S., 2011. A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image. Comput. Med. Imag. Graph., 35(5):383-397. doi:10.1016/j.comp medimag.2010.12.001
    • (2011) Comput. Med. Imag. Graph. , vol.35 , Issue.5 , pp. 383-397
    • Ji, Z.X.1    Sun, Q.S.2    Xia, D.S.3
  • 22
    • 0141857203 scopus 로고    scopus 로고
    • An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation
    • doi:10.1109/TMI.2003.816956
    • Liew, A.W., Yan, H., 2003. An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation. IEEE Trans. Med. Imag., 22(9):1063-1075. doi:10.1109/TMI.2003.816956
    • (2003) IEEE Trans. Med. Imag. , vol.22 , Issue.9 , pp. 1063-1075
    • Liew, A.W.1    Yan, H.2
  • 23
    • 33746015928 scopus 로고    scopus 로고
    • Current methods in the automatic tissue segmentation of 3D magnetic resonance brain images
    • doi:10. 2174/157340506775541604
    • Liew, A.W., Yan, H., 2006. Current methods in the automatic tissue segmentation of 3D magnetic resonance brain images. Curr. Med. Imag. Rev., 2(1):91-103. doi:10. 2174/157340506775541604
    • (2006) Curr. Med. Imag. Rev. , vol.2 , Issue.1 , pp. 91-103
    • Liew, A.W.1    Yan, H.2
  • 24
    • 77957680810 scopus 로고    scopus 로고
    • Switching-based filter based on Dempster's combination rule for image processing
    • doi:10.1016/j.ins.2010.08.011
    • Lin, T.C., 2010. Switching-based filter based on Dempster's combination rule for image processing. Inf. Sci., 180(24): 4892-4908. doi:10.1016/j.ins. 2010.08.011
    • (2010) Inf. Sci. , vol.180 , Issue.24 , pp. 4892-4908
    • Lin, T.C.1
  • 25
    • 0030153642 scopus 로고    scopus 로고
    • Deformable models in medical image analysis: A survey
    • doi:10.1016/S1361-8415(96)80007-7
    • McInerney, T., Terzopoulos, D., 1996. Deformable models in medical image analysis: a survey. Med. Image Anal., 1(2):91-108. doi:10.1016/S1361-8415(96) 80007-7
    • (1996) Med. Image Anal. , vol.1 , Issue.2 , pp. 91-108
    • McInerney, T.1    Terzopoulos, D.2
  • 26
    • 0032632272 scopus 로고    scopus 로고
    • Multiscale segmentation of three-dimensional MR brain images
    • doi:10.1023/A:1008070000018
    • Niessen, W.J., Vincken, K.L., Weickert, J., Romeny, M.T.H., Viergever, M.A., 1999. Multiscale segmentation of three-dimensional MR brain images. Int. J. Comput. Vis., 31(2/3):185-202. doi:10.1023/A:1008070000018
    • (1999) Int. J. Comput. Vis. , vol.31 , Issue.2-3 , pp. 185-202
    • Niessen, W.J.1    Vincken, K.L.2    Weickert, J.3    Romeny, M.T.H.4    Viergever, M.A.5
  • 27
    • 0032843554 scopus 로고    scopus 로고
    • An adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities
    • doi:10.1016/S0167-8655(98)00121-4
    • Pham, D.L., Prince, J.L., 1999a. An adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities. Pattern Recogn. Lett., 20(1): 57-68. doi:10.1016/S0167-8655(98)00121-4
    • (1999) Pattern Recogn. Lett. , vol.20 , Issue.1 , pp. 57-68
    • Pham, D.L.1    Prince, J.L.2
  • 28
    • 0033181293 scopus 로고    scopus 로고
    • Adaptive fuzzy segmentation of magnetic resonance images
    • doi:10.1109/42.802752
    • Pham, D.L., Prince, J.L., 1999b. Adaptive fuzzy segmentation of magnetic resonance images. IEEE Trans. Med. Imag., 18(9):737-752. doi:10.1109/42.802752
    • (1999) IEEE Trans. Med. Imag. , vol.18 , Issue.9 , pp. 737-752
    • Pham, D.L.1    Prince, J.L.2
  • 29
    • 0034575445 scopus 로고    scopus 로고
    • A survey of current methods in medical image segmentation
    • doi:10.1146/annurev.bioeng. 2.1.315
    • Pham, D.L., Xu, C., Prince, J.L., 2000. A survey of current methods in medical image segmentation. Ann. Rev. Biomed. Eng., 2(1):315-337. doi:10.1146/annurev.bioeng. 2.1.315
    • (2000) Ann. Rev. Biomed. Eng. , vol.2 , Issue.1 , pp. 315-337
    • Pham, D.L.1    Xu, C.2    Prince, J.L.3
  • 31
    • 0343844456 scopus 로고    scopus 로고
    • Transferable belief model in fault diagnosis
    • doi:10.1016/S0952-1976(99)00030-5
    • Rakar, A., Juricic, D., Ballé, P., 1999. Transferable belief model in fault diagnosis. Eng. Appl. Artif. Intell., 12(5): 555-567. doi:10.1016/S0952-1976(99)00030-5
    • (1999) Eng. Appl. Artif. Intell. , vol.12 , Issue.5 , pp. 555-567
    • Rakar, A.1    Juricic, D.2    Ballé, P.3
  • 32
    • 78049238752 scopus 로고    scopus 로고
    • A joint Bayesian framework for MR brain scan tissue and structure segmentation based on distributed Markovian agents
    • doi:10. 1007/978-3-642-14464-6-5
    • Scherrer, B., Forbes, F., Garbay, C., Dojat, M., 2010. A joint Bayesian framework for MR brain scan tissue and structure segmentation based on distributed Markovian agents. Comput. Intell. Healthcare 4, 309:81-101. doi:10. 1007/978-3-642-14464-6-5
    • (2010) Comput. Intell. Healthcare 4 , vol.309 , pp. 81-101
    • Scherrer, B.1    Forbes, F.2    Garbay, C.3    Dojat, M.4
  • 34
    • 25844489923 scopus 로고    scopus 로고
    • MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization
    • doi:10.1109/TITB. 2005.847500
    • Shen, S., Sandham, W., Granat, M., Sterr, A., 2005. MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization. IEEE Trans. Inf. Technol. Biomed., 9(3):459-467. doi:10.1109/TITB. 2005.847500
    • (2005) IEEE Trans. Inf. Technol. Biomed. , vol.9 , Issue.3 , pp. 459-467
    • Shen, S.1    Sandham, W.2    Granat, M.3    Sterr, A.4
  • 35
    • 0028339167 scopus 로고
    • Sources of intensity nonuniformity in spin echo images at 1.5 T
    • doi:10.1002/mrm.1910320117
    • Simmons, A., Tofts, P.S., Barker, G.J., Arridge, S.R., 1994. Sources of intensity nonuniformity in spin echo images at 1.5 T. Magn. Reson. Med., 32(1):121-128. doi:10.1002/mrm.1910320117
    • (1994) Magn. Reson. Med. , vol.32 , Issue.1 , pp. 121-128
    • Simmons, A.1    Tofts, P.S.2    Barker, G.J.3    Arridge, S.R.4
  • 36
    • 24344477133 scopus 로고    scopus 로고
    • An intelligent modified fuzzy c-means based algorithm for bias estimation and segmentation of brain MRI
    • doi:10.1016/j.patrec.2005.03.019
    • Siyal, M.Y., Yu, L., 2005. An intelligent modified fuzzy c-means based algorithm for bias estimation and segmentation of brain MRI. Pattern Recogn. Lett., 26(13): 2052-2062. doi:10.1016/j.patrec.2005.03.019
    • (2005) Pattern Recogn. Lett. , vol.26 , Issue.13 , pp. 2052-2062
    • Siyal, M.Y.1    Yu, L.2
  • 37
    • 0031987382 scopus 로고    scopus 로고
    • A nonparametric method for automatic correction of intensity nonuniformity in MRI data
    • doi:10.1109/42.668698
    • Sled, J.G., Zijdenbos, A.P., Evans, A.C., 1998. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans. Med. Imag., 17(1):87-97. doi:10.1109/42.668698
    • (1998) IEEE Trans. Med. Imag. , vol.17 , Issue.1 , pp. 87-97
    • Sled, J.G.1    Zijdenbos, A.P.2    Evans, A.C.3
  • 38
    • 0033623981 scopus 로고    scopus 로고
    • Parametric estimate of intensity inhomogeneities applied to MRI
    • doi:10. 1109/42.845174
    • Styner, M., Brechbuhler, C., Szekely, G., Gerig, G., 2000. Parametric estimate of intensity inhomogeneities applied to MRI. IEEE Trans. Med. Imag., 19(3):153-165. doi:10. 1109/42.845174
    • (2000) IEEE Trans. Med. Imag. , vol.19 , Issue.3 , pp. 153-165
    • Styner, M.1    Brechbuhler, C.2    Szekely, G.3    Gerig, G.4
  • 39
    • 79151476013 scopus 로고    scopus 로고
    • Knitted fabric defect classification for uncertain labels based on Dempster-Shafer theory of evidence
    • doi:10.1016/j.eswa.2010.10.032
    • Tabassian, M., Ghaderi, R., Ebrahimpour, R., 2011. Knitted fabric defect classification for uncertain labels based on Dempster-Shafer theory of evidence. Expert Syst. Appl., 38(5):5259-5267. doi:10.1016/j.eswa.2010.10.032
    • (2011) Expert Syst. Appl. , vol.38 , Issue.5 , pp. 5259-5267
    • Tabassian, M.1    Ghaderi, R.2    Ebrahimpour, R.3
  • 40
    • 80054898828 scopus 로고    scopus 로고
    • Combination of multiple diverse classifiers using belief functions for handling data with imperfect labels
    • doi:10.1016/j.eswa.2011. 06.061
    • Tabassian, M., Ghaderi, R., Ebrahimpour, R., 2012. Combination of multiple diverse classifiers using belief functions for handling data with imperfect labels. Expert Syst. Appl., 39(2):1698-1707. doi:10.1016/j.eswa.2011. 06.061
    • (2012) Expert Syst. Appl. , vol.39 , Issue.2 , pp. 1698-1707
    • Tabassian, M.1    Ghaderi, R.2    Ebrahimpour, R.3
  • 42
    • 73649085443 scopus 로고    scopus 로고
    • Multi-stream speech recognition based on Dempster-Shafer combination rule
    • doi:10.1016/j.specom.2009.10.002
    • Valente, F., 2010. Multi-stream speech recognition based on Dempster-Shafer combination rule. Speech Commun., 52(3):213-222. doi:10.1016/j.specom.2009.10.002
    • (2010) Speech Commun. , vol.52 , Issue.3 , pp. 213-222
    • Valente, F.1
  • 43
    • 55649121609 scopus 로고    scopus 로고
    • A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints
    • doi:10.1016/j.compmed imag.2008.08.004
    • Wang, J., Kong, J., Lu, Y., Qi, M., Zhang, B., 2008. A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints. Comput. Med. Imag. Graph., 32(8):685-698. doi:10.1016/j.compmed imag.2008.08.004
    • (2008) Comput. Med. Imag. Graph. , vol.32 , Issue.8 , pp. 685-698
    • Wang, J.1    Kong, J.2    Lu, Y.3    Qi, M.4    Zhang, B.5
  • 45
    • 0033281234 scopus 로고    scopus 로고
    • MR brain image segmentation using fuzzy clustering
    • doi:10.1109/FUZZY.1999.793060
    • Yoon, O.K., Kwak, D.M., Kim, D.W., Park, K.H., 1999. MR Brain Image Segmentation Using Fuzzy Clustering. Proc. IEEE Int. Fuzzy Systems Conf., 2:853-857. doi:10.1109/FUZZY.1999.793060
    • (1999) Proc. IEEE Int. Fuzzy Systems Conf. , vol.2 , pp. 853-857
    • Yoon, O.K.1    Kwak, D.M.2    Kim, D.W.3    Park, K.H.4
  • 46
    • 4444347719 scopus 로고    scopus 로고
    • A novel kernelized fuzzy c-means algorithm with application in medical image segmentation
    • doi:10. 1016/j.artmed.2004.01.012
    • Zhang, D.Q., Chen, S.C., 2004. A novel kernelized fuzzy c-means algorithm with application in medical image segmentation. Artif. Intell. Med., 32(1):37-50. doi:10. 1016/j.artmed.2004.01.012
    • (2004) Artif. Intell. Med. , vol.32 , Issue.1 , pp. 37-50
    • Zhang, D.Q.1    Chen, S.C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.