Psychiatry Research: Neuroimaging
Volume 164, Issue 2 , Pages 172-177 , 30 November 2008

Cross-validation of brain segmentation by SPM5 and SIENAX

  • Hedok Lee

      Affiliations

    • Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, USA
    • ,
  • Isak Prohovnik

      Affiliations

    • Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, USA
    • Department of Radiology, Mount Sinai School of Medicine, New York, NY, USA
    • Corresponding Author InformationCorresponding author. MIRECC, Bronx VA Medical Center, 130 West Kingsbridge Road, Bronx, NY 10468, USA. Tel.: +1 718 584 9000x3629; fax: +1 801 659 8648.

Received 16 January 2007 ,Revised 12 September 2007 ,Accepted 22 December 2007.

References 

  1. Ashburner J, Friston KJ. Unified segmentation. Neuroimage. 2005;26:839–851
  2. Blatter DD, Bigler ED, Gale SD, Johnson SC, Anderson CV, Burnett BM, et al. Quantitative volumetric analysis of brain MR: normative database spanning 5 decades of life. American Journal of Neuroradiology. 1995;16:241–251
  3. Brunetti A, Postiglione A, Tedeschi E, Ciarmiello A, Quarantelli M, Covelli EM, et al. Measurement of global brain atrophy in Alzheimer's disease with unsupervised segmentation of spin-echo MRI studies. Journal of Magnetic Resonance Imaging. 2000;11:260–266
  4. Dice LR. Measures of the amount of ecologic association between species. Ecology. 1945;26:297–302
  5. Douaud G, Gaura V, Ribeiro MJ, Lethimonnier F, Maroy R, Verny C, et al. Distribution of grey matter atrophy in Huntington's disease patients: a combined ROI-based and voxel-based morphometric study. Neuroimage. 2006;32:1562–1575
  6. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341–355
  7. Fischl B, Salat DH, van der Kouwe AJ, Makris N, Segonne F, Quinn BT, et al. Sequence-independent segmentation of magnetic resonance images. Neuroimage. 2004;23:S69–S84
  8. Fulbright RK, Kingsley PB, Guo X, Hoffmann C, Kahana E, Chapman JC, et al. The imaging appearance of Creutzfeldt–Jakob disease caused by the E200K mutation. Magnetic Resonance Imaging. 2006;24:1121–1129
  9. Ge Y, Grossman RI, Babb JS, Rabin ML, Mannon LJ, Kolson DL. Age-related total gray matter and white matter changes in normal adult brain. Part I: volumetric MR imaging analysis. American Journal of Neuroradiology. 2002;23:1327–1333
  10. Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS. A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage. 2001;14:21–36
  11. Guillemaud R, Brady M. Estimating the bias field of MR images. IEEE Transactions on Medical Imaging. 1997;16:238–251
  12. Karas GB, Burton EJ, Rombouts SA, van Schijndel RA, O'Brien JT, Scheltens P, et al. A comprehensive study of gray matter loss in patients with Alzheimer's disease using optimized voxel-based morphometry. Neuroimage. 2003;18:895–907
  13. Makris N, Kaiser J, Haselgrove C, Seidman LJ, Biederman J, Boriel D, et al. Human cerebral cortex: a system for the integration of volume- and surface-based representations. Neuroimage. 2006;33:139–153
  14. Miller DH, Barkhof F, Frank JA, Parker GJ, Thompson AJ. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain. 2002;125:1676–1695
  15. Pelletier D, Garrison K, Henry R. Measurement of whole-brain atrophy in multiple sclerosis. Journal of Neuroimaging. 2004;14:11S–19S
  16. Reiss AL, Hennessey JG, Rubin M, Beach L, Abrams MT, Warsofsky IS, et al. Reliability and validity of an algorithm for fuzzy tissue segmentation of MRI. Journal of Computer Assisted Tomography. 1998;22:471–479
  17. Resnick SM, Goldszal AF, Davatzikos C, Golski S, Kraut MA, Metter EJ, et al. One-year age changes in MRI brain volumes in older adults. Cerebral Cortex. 2000;10:464–472
  18. Smith CD, Chebrolu H, Wekstein DR, Schmitt FA, Markesbery WR. Age and gender effects on human brain anatomy: a voxel-based morphometric study in healthy elderly. Neurobiology of Aging. 2007;28:1075–1087
  19. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23 Suppl 1:S208–S219
  20. Smith SM, Zhang Y, Jenkinson M, Chen J, Matthews PM, Federico A, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage. 2002;17:479–489
  21. Taki Y, Goto R, Evans A, Zijdenbos A, Neelin P, Lerch J, et al. Voxel-based morphometry of human brain with age and cerebrovascular risk factors. Neurobiology of Aging. 2004;25:455–463
  22. In:  Tofts P editors. Quantitative MRI of the Brain: Measuring Changes Caused by Disease. West Sussex: John Wiley & Sons; 2003;
  23. Van Leemput K, Maes F, Vandermeulen D, Suetens P. Automated model-based bias field correction of MR images of the brain. IEEE Transactions on Medical Imaging. 1999;18:885–896
  24. Van Leemput K, Maes F, Vandermeulen D, Suetens P. Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging. 1999;18:897–908
  25. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Transactions on Medical Imaging. 2001;20:45–57
  26. Zijdenbos A, Dawant BM, Margolin RA, Palmer AC. Morphometric analysis of white matter. Lesions in MR images: method and validation. IEEE Transactions on Medical Imaging. 1994;13:716–724
  27. Zivadinov R, Grop A, Sharma J, Bratina A, Tjoa CW, Dwyer M, et al. Reproducibility and accuracy of quantitative magnetic resonance imaging techniques of whole-brain atrophy measurement in multiple sclerosis. Journal of Neuroimaging. 2005;15:27–36

PII: S0925-4927(07)00258-2

doi: 10.1016/j.pscychresns.2007.12.008

Psychiatry Research: Neuroimaging
Volume 164, Issue 2 , Pages 172-177 , 30 November 2008

Article Tools

* Image Usage & Resolution