Segmentation of MRI brain scans using non-uniform partial volume densities

NeuroImage

Volumn 49, Issue 1, 2010, Pages 467-477

  Brouwer, Rachel M ^a   Hulshoff Pol, Hilleke E ^a   Schnack, Hugo G ^a  

^a UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

Author keywords

Gray white separation; Human brain; MRI; Non uniform distribution; Partial volume effect; Reliability; Segmentation

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BRAIN SIZE; CEREBROSPINAL FLUID; COMPUTER SIMULATION; CONTROLLED STUDY; GRAY MATTER; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; RELIABILITY; WHITE MATTER;

ALGORITHMS; BRAIN; CEREBROSPINAL FLUID; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; PHANTOMS, IMAGING; REPRODUCIBILITY OF RESULTS;

EID: 70349965988     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2009.07.041     Document Type: Article

References (46)

1. Agartz I., Okuguwa G., Nordström M., Greitz D., Magnotta V., and Sedvall G. Reliability and reproducibility of brain tissue volumetry from segmented MR scans. Eur. Arch. Psychiatry Clin. Neurosci. 251 (2001) 255-261
2. Anbeek P., Vinken K.L., van Bochove G.S., van Osch M.J., and van der Grond J. Probabilistic segmentation of brain tissue in MR imaging. NeuroImage 27 (2005) 795-804
3. Ashburner J., and Friston K. Multimodal image coregistration and partitioning - a unified framework. NeuroImage 6 (1997) 209-217
4. Atkinson K.A. An Introduction to Numerical Analysis. 2nd ed. (1989), John Wiley & Sons
5. Aubert-Broche B., Evans A.C., and Collins L. A new improved version of the realistic digital brain phantom. NeuroImage 32 (2006) 138-145
6. Aubert-Broche B., Griffin M., Pike G.B., Evans A.C., and Collins D.L. Twenty new digital brain phantoms for creation of validation image data bases. IEEE Trans. Med. Imag. 25 (2006) 1410-1416
7. Bach Cuadra M., Cammoun L., Butz T., Cuisenaire O., and Thiran J.P. Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images. IEEE Trans. Med. Imag. 24 (2005) 1548-1565
8. Bello F., Colchester A.C.F., and Röll S.A. A geometry- and intensity-based partial volume correction for MRI volumetric studies. Comput. Med. Imaging Graph. 22 (1998) 123-132
9. Bricq S., Collet C., and Armspach J. Unifying framework for multimodal brain MRI segmentation based on hidden Markov chains. Med. Image Anal. 12 (2008) 639-652
10. Cantarella, J., Piatek, M., aug 2004. tsnnls - a sparse nonnegative least-squares solver. URL:http://www.cs.duq.edu/piatek/tsnnls/.
11. Chard D., Parker G., Griffin C., Thompson A., and Miller D. The reproducibility and sensitivity of brain tissue volume measurements derived from an SPM-based segmentation methodology. J. Magn. Res. Imaging 15 (2002) 259-267
12. Choi H.S., Haynor D.R., and Kim Y. Partial volume tissue classification of multichannel magnetic resonance images - a mixel model. IEEE Trans. Med. Imag. 10 (1991) 395-407
13. Cocosco C.A., Kollokian V., Kwan R.K.S., and Evans A.C. Brainweb: online interface to a 3D MRI simulated brain database. Proceedings of 3-rd International Conference on Functional Mapping of the Human Brain. Vol (1997), NeuroImage, Copenhagen 5
14. Cocosco C.A., Zijdenbos A.P., and Evans A.C. A fully automatic and robust brain MRI tissue classification method. Med. Image Anal. 7 (2003) 513-527
15. Collins D.L., Holmes C.J., Peters T.M., and Evans A.C. Automatic 3-d model-based neuroanatomical segmentation. Hum. Brain Mapp. 3 (1995) 190-208
16. Collins D.L., Zijdenbos A.P., Kollokian V., Sled J.G., Kabani N.J., Holmes C.J., and Evans A.C. Design and construction of a realistic digital brain phantom. IEEE Trans. Med. Imag. 17 (1998) 368-463
17. Dice L.R. Measures of the amount of ecologic association between species. Ecology 26 (1945) 297-302
18. Fischl B., Salat D.H., van der Kouwe A.J., Makris N., Ségonne F., Quinn B.T., and Dale A.M. Sequence-independent segmentation of magnetic resonance images. NeuroImage 23 (2004) S69-S84
19. González Ballester M., Zisserman A.P., and Brady M. Estimation of partial volume effect in MRI. Med. Image Anal. 6 (2002) 389-405
20. Grabowski T.J., Frank R.J., Szumski N.R., Brown C.K., and Damasio H. Validation of partial tissue segmentation of single-channel magnetic resonance images of the brain. NeuroImage 12 (2000) 640-656
21. Gudbjartsson H., and Patz S. The Rician distribution of MRI data. Magn. Reson. Med. 34 (1995) 910-914
22. Gur R., Turetsky B., Matsui M., Yan M., Bilker W., Hughett P., and Gur R. Sex differences in brain gray and white matter in healthy young adults: correlations with cognitive performance. J. Neurosci. 19 (1999) 4065-4072
23. Kovacevic N., Lobaugh N.J., Bronskill M.J., Levine B., Feinstein A., and Black S.E. A robust method for extraction and automatic segmentation of brain images. NeuroImage 17 (2002) 1087-1100
24. Kreyszig E. Advanced engineering mathematics. 7th ed. (1993), John Wiley and Sons 286-287
25. Kwan R.K.S., Evans A.C., and Pike G.B. An extensible MRI simulator for post-processing evaluation, Visualization in Biomedical Computing Edition. Vol. 1131 of Lecture Notes in Computer Science (1996), Springer-Verlag 135-140
26. Laidlaw D.H., Fleischer K.W., and Barr A.H. Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms. IEEE Trans. Med. Imag. 17 (1998) 74-86
27. Leemput K., Maes F., Vandermeulen D., and Suetens P. A unifying framework for partial volume segmentation of brain MR images. IEEE Trans. Med. Imag. 22 (2003) 105-119
28. Li X., Li L., Lu H., and Liang Z. Partial volume segmentation of brain magnetic resonance images based on maximum a posteriori probability. Med. Phys. 32 (2005) 2337-2345
29. Manjón J.V., Tohka J., García-Martí G., Carbonell-Caballero J., Lull J.J., Martí-Bonmatí L., and Robles M. Robust MRI brain tissue parameter estimation by multistage outlier rejection. Magn. Reson. Med. 59 (2008) 866-873
30. McGraw K.O., and Wong S. Forming inferences about some intraclass correlation coefficients. Psycological Methods 1 (1996) 30-46
31. Nelder J., and Mead R. A simplex method for function minimization. Comput. J. 7 (1965) 308-315
32. Niessen, W.J., 1997. Multiscale medical image analysis. Ph.D. thesis, University of Utrecht, the Netherlands.
33. Portugal L.F., Júdice J.J., and Vicente L.N. A comparison of block pivoting and interior-point algorithms for linear least squares problems with nonnegative variables. Math. Comp. 63 208 (1994) 625-643
34. Röll A., Colchester A.C.F., Summers P.E., and Griffin L.D. Intensity-based object extraction from 3D medical images including a correction of partial volume errors. Proceedings of the 5th British Machine Vision Conference (1994), BMVC Press 205-214
35. Ruan S., Jaggi C., Xue J., Fadili J., and Bloyet D. Brain tissue classification of magnetic resonance images using partial volume modeling. IEEE Trans. Med. Imag. 19 (2000) 1187-1479
36. Santago P., and Gage H.D. Quantification of MR brain images by mixture density and partial volume modeling. IEEE Trans. Med. Imag. 12 (1993) 566-574
37. Schnack H.G., Hulshoff Pol H.E., Baaré W.F.C., Staal W.G., Viergever M.A., and Kahn R.S. Automated separation of gray and white matter from MR images of the human brain. NeuroImage 13 (2001) 230-237
38. Schnack H.G., van Haren N.E., Hulshoff Pol H.E., Picchioni M., Weisbrod M., Sauer H., Huttunen M., Murray R., and Kahn R.S. Reliability of brain volumes from multicenter MRI acquisition: a calibration study. Hum. Brain Mapp. 22 (2004) 312-320
39. Schroeter P., Vesin J.M., Langenberger T., and Meuli R. Robust parameter estimation of intensity distributions for brain magnetic resonance images. IEEE Trans. Med. Imag. 17 (1998) 172-186
40. Shattuck D.W., Sandor-Leahy S.R., Schaper K.A., Rottenberg D.A., and Leahy R.M. Magnetic resonance image tissue classification using a partial volume model. NeuroImage 13 (2001) 856-876
41. Sled J.G., Zijdenbos A.P., and Evans A.C. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans. Med. Imag. 17 (1998) 87-97
42. Song T., Gasparovic C., Andreasen N., Bockholt J., Jamshidi M., Lee R.R., and Huang M. A hybrid tissue segmentation approach for brain MR images. Med. Biol. Eng. Comput. 44 (2006) 242-249
43. Talairach J., and Tournoux P. Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: an Approach to Cerebral Imaging (1988), Thieme, New York
44. Tohka J., Krestyannikov E., Dinov I., Graham A., Shattuck D., Ruosalainen U., and Toga A.W. Genetic algorithms for finite mixture model based tissue classification in neuroimaging. IEEE Trans. Med. Imaging 26 (2007) 696-711
45. Tohka J., Zijdenbos A., and Evans A. Fast and robust parameter estimation for statistical partial volume models in brain MRI. NeuroImage 23 (2004) 84-97
46. Zhang Y., Brady M., and Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imag. 20 (2001) 45-57