Correction of inhomogeneous magnetic resonance images using multiscale retinex for segmentation accuracy improvement

Biomedical Signal Processing and Control

Volumn 7, Issue 2, 2012, Pages 129-140

  Chao, Wen Hung ^a   Lai, Hsin Yi ^b   Shih, Yen Yu I ^c   Chen, You Yin ^d   Lo, Yu Chun ^e   Lin, Sheng Huang ^e,f   Tsang, Siny ^g   Wu, Robby ^h   Jaw, Fu Shan ^e  

^a YUANPEI UNIVERSITY   (Taiwan)

^b NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^c UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT SAN ANTONIO   (United States)

^d NATIONAL YANG MING UNIVERSITY   (Taiwan)

^e NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^f TZU CHI UNIVERSITY   (Taiwan)

^g UNIVERSITY OF VIRGINIA   (United States)

^h PHILADELPHIA COLLEGE OF OSTEOPATHIC MEDICINE   (United States)

Author keywords

Boosted decision tree; Brain tissue; Multiscale retinex; Segmentation; Spatial feature

Indexed keywords

BRAIN; CEREBROSPINAL FLUID; DECISION TREES; IMAGE SEGMENTATION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MAXIMUM PRINCIPLE; TISSUE; TREES (MATHEMATICS);

BOOSTED DECISION TREES; BRAIN TISSUE; BRAIN TISSUE SEGMENTATIONS; CEREBRAL SPINAL FLUIDS; CLINICAL IMAGE SEGMENTATION; EXPECTATION-MAXIMIZATION ALGORITHMS; MULTI-SCALE RETINEX; SPATIAL FEATURES;

IMAGE ENHANCEMENT;

ALGORITHM; ARTICLE; BRAIN TISSUE; BRAIN TISSUE SEGMENTATION; CEREBROSPINAL FLUID; DECISION TREE; EXPECTATION MAXIMIZATION ALGORITHM; GRAY MATTER; HUMAN; HUMAN TISSUE; MULTISCALE RETINEX; NUCLEAR MAGNETIC RESONANCE; PRIORITY JOURNAL; PROCEDURES; SIMULATION; WHITE MATTER;

EID: 84857356581     PISSN: 17468094     EISSN: 17468108     Source Type: Journal    
DOI: 10.1016/j.bspc.2011.04.001     Document Type: Article

References (37)

1. D. Dong-yong, B. Condon, D. Hadley, R. Rampling, and G. Teasdale Intracranial deformation caused by brain tumors: assessment of 3-D surface by magnetic resonance imaging IEEE Trans. Med. Imaging 12 1993 693 702 (Pubitemid 2022623)
2. M.R. Kaus, S.K. Warfield, A. Nabavi, P.M. Black, F.A. Jolesz, and R. Kikinis Automated segmentation of MR images of brain tumors Radiology 218 2001 586 591 (Pubitemid 32121080)
3. M. Prastawa, E. Bullitt, S. Ho, and G. Gerig A brain tumor segmentation framework based on outlier detection Med. Image Anal. 8 2004 275 283 (Pubitemid 39185911)
4. W.B. Dou, S. Ruan, Y.P. Chen, D. Bloyet, and J.M. Constans A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images Image Vis. Comput. 25 2007 164 171 (Pubitemid 44873142)
5. L. Zhengrong, J.R. MacFall, and D.P. Harrington Parameter estimation and tissue segmentation from multispectral MR images IEEE Trans. Med. Imaging 13 1994 441 449
6. C. Baillard, P. Hellier, and C. Barillot Segmentation of brain 3D MR images using level sets and dense registration Med. Image Anal. 5 2001 185 194 (Pubitemid 35282803)
7. C. Lukas, H.K. Hahn, B. Bellenberg, J. Rexilius, G. Schmid, and S.K. Schimrigk Sensitivity and reproducibility of a new fast 3D segmentation technique for clinical MR-based brain volumetry in multiple sclerosis Neuroradiology 46 2004 906 915 (Pubitemid 40057973)
8. T. Song, C. Gasparovic, N. Andreasen, J. Bockholt, M. Jamshidi, and R.R. Lee A hybrid tissue segmentation approach for brain MR images Med. Biol. Eng. Comput. 44 2006 242 249 (Pubitemid 43949718)
9. S. Shen, W. Sandham, M. Granat, and A. Sterr MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization IEEE Trans. Inf. Technol. Biomed. 9 2005 459 467 (Pubitemid 41388212)
10. H.A. Vrooman, C.A. Cocosco, F. van der Lijn, R. Stokking, M.A. Ikram, and M.W. Vernooij Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification Neuroimage 37 2007 71 81 (Pubitemid 47068998)
11. J.V. Manjon, J. Tohka, G. Garcia-Marti, J. Carbonell-Caballero, J.J. Lull, and L. Marti-Bonmati Robust MRI brain tissue parameter estimation by multistage outlier rejection Magn. Reson. Med. 59 2008 866 873 (Pubitemid 351501953)
12. L.Q. Zhou, Y.M. Zhu, C. Bergot, A.M. Laval-Leantet, V. Bousson, and J.D. Laredo A method of radio-frequency inhomogeneity correction for brain tissue segmentation in MRI Comput. Med. Imaging Graph. 25 2001 379 389 (Pubitemid 32506865)
13. J.D. Gispert, S. Reig, J. Pascau, J.J. Vaquero, P. García-Barreno, and M. Desco Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error Hum. Brain Mapp. 22 2004 133 144 (Pubitemid 38738036)
14. M. Garcia-Sebastian, C. Hernandez, and A. d'Anjou Robustness of an adaptive MRI segmentation algorithm parametric intensity inhomogeneity modeling Neurocomputing 72 2009 2146 2152
15. W.H. Chao, Y.Y. Chen, C.W. Cho, S.H. Lin, Y.Y. Shih, and S. Tsang Improving segmentation accuracy for magnetic resonance imaging using a boosted decision tree J. Neurosci. Methods 175 2008 206 217
16. E. Land An alternative technique for the computation of the designator in the retinex theory of color vision Proc. Natl. Acad. Sci. U. S. A. 83 1986 3078 3080
17. A.C. Hurlbert, and T. Poggio Synthesizing a color algorithm from examples Science 239 1988 482 485
18. A.C. Hurlbert, The computation of color, Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MA, 1989.
19. A. Moore, J. Allman, and R.M. Goodman A real-time neural system for color constancy IEEE Trans. Neural Netw. 2 1991 237 247
20. A. Moore, G. Fox, J. Allman, and R.M. Goodman A VLSI neural network for color constancy D.S. Touretzky, R. Lippman, E.S. Mateo, Advances in Neural Information Processing 3 1991 Morgan Kaufmann CA 370 376
21. D.J. Jobson, Z. Rahman, and G.A. Woodell Properties and performance of a center/surround retinex IEEE Trans. Image Process. 6 1997 451 462 (Pubitemid 127768376)
22. D.J. Jobson, Z. Rahman, and G.A. Woodell A multiscale retinex for bridging the gap between color images and the human observation of scenes IEEE Trans. Image Process. 6 1997 965 976 (Pubitemid 127772284)
23. K.A. Grajski, L. Breiman, G. Viana Di Prisco, and W.J. Freeman Classification of EEG spatial patterns with a tree-structured methodology: CART IEEE Trans. Biomed. Eng. 33 1986 1076 1086 (Pubitemid 17517254)
24. H.R. Bittencourt, and R.T. Clarke Use of classification and regression trees (CART) to classify remotely-sensed digital images Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, vol. 6 2003 3751 3753
25. S. Hautaniemi, S. Kharait, A. Iwabu, A. Wells, and D.A. Lauffenburger Modeling of signal-response cascades using decision tree analysis Bioinformatics 21 2005 2027 2035 (Pubitemid 40668041)
26. W.H. Chao, Y.Y. Chen, S.H. Lin, Y.Y.I. Shih, and S. Tsang Automatic segmentation of magnetic resonance images using a decision tree with spatial information Comput. Med. Imaging Graph. 33 2009 111 121
27. J.R. Quinlan C4. 5: Programs for Machine Learning 1993 Morgan Kaufmann San Mateo, CA
28. J.R. Quinlan Improved use of continuous attributes in C4.5 J. Artif. Intell. Res. 4 1996 77 90 (Pubitemid 126646149)
29. J.R. Quinlan Data Mining Tools See5 and C5. 0 2003 RuleQuest Research Austria http://www.rulequest.com/see5-info.html
30. J.R. Quinlan Induction of decision tree Mach. Learn. 1 1986 81 106
31. J. Macek Incremental learning of ensemble classifiers on ECG data Proceedings of the 18th IEEE Symposium on Computer-Based Medical System (CBMS'05) 2005
32. D. Arditi, and T. Pulket Predicting the outcome of construction litigation using boosted decision trees J. Comput. Civil Eng. 19 2005 387 393 (Pubitemid 41441369)
33. U. Amato, M. Larobina, A. Antoniadis, and B. Alfano Segmentation of magnetic resonance brain images through discriminant analysis J. Neurosci. Methods 131 2003 65 74 (Pubitemid 37491461)
34. W.M. Wells, W.E.L. Grimson, R. Kikinis, and F.A. Jolesz Adaptive segmentation of MRI data IEEE Trans. Med. Imaging 15 1996 429 442 (Pubitemid 126780333)
35. X. Li, L. Li, H. Lu, and Z. Liang Partial volume segmentation of brain magnetic resonance images based on maximum a posteriori probability Med. Phys. 32 2005 2337 2345 (Pubitemid 41023193)
36. Z.Q. Yu, Y. Zhu, J. Yang, and Y.M. Zhu A hybrid region-boundary model for cerebral cortical segmentation in MRI Comput. Med. Imaging Graph. 30 2006 197 208 (Pubitemid 43817483)
37. R.G. Boyes, J.L. Gunter, C. Frost, A.L. Janke, T. Yeatman, and D.L.G. Hill Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils NeuroImage 39 2008 1752 1762