The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Measuring the thickness of the human cerebral cortex from magnetic resonance images
Open accessAbstract
Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test–retest studies, as well as by comparison of cross-subject regional thickness measures with published values.
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Cites
The Laplacian pyramid as a compact image code
Burt, P., & Adelson, E. (1983) · IEEE Transactions on Communications · doi:10.1109/tcom.1983.1095851 · Cited by 6,077
Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease
Jack, C. R., Petersen, R. C., Xu, Y. C., Waring, S. C., O'Brien, P. C., Tangalos, E. G., Smith, G. E., Ivnik, R. J., & Kokmen, E. (1997) · Neurology · doi:10.1212/wnl.49.3.786 · Cited by 1,128
Frequency of hippocampal formation atrophy in normal aging and Alzheimer's disease
De Leon, M. J., George, A. E., Golomb, J., Tarshish, C., Convit, A., Kluger, A., De Santi, S., Mc Rae, T., Ferris, S. H., Reisberg, B., et al. (1997) · Neurobiology of Aging · doi:10.1016/s0197-4580(96)00213-8 · Cited by 429
Pathologic heterogeneity in clinically diagnosed corticobasal degeneration
Boeve, B. F., Maraganore, D. M., Parisi, J. E., Ahlskog, J. E., Graff-Radford, N., Caselli, R. J., Dickson, D. W., Kokmen, E., & Petersen, R. C. (1999) · Neurology · doi:10.1212/wnl.53.4.795 · Cited by 417
Kaye, J. A., Swihart, T., Howieson, D., Dame, A., Moore, M. M., Karnos, T., Camicioli, R., Ball, M., Oken, B., & Sexton, G. (1997) · Neurology · doi:10.1212/wnl.48.5.1297 · Cited by 399
Research works printed but not linked: 35
- 10.1016/B978-0-12-547625-6.50027-1 · DOI
- C von Economo The Cytoarchitectonics of the Human Cerebral Cortex (Oxford Univ. Press, London, 1929).
- K Brodmann Vergleichende Lokalisationslehre der Großhirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues (Barth, Leipzig, Germany, 1909).
- 10.1073/pnas.93.24.13547 · DOI
- G B Frisoni, A Beltramello, C Weiss, C Geroldi, A Bianchetti, M Trabucchi Am J Neuroradiol 17, 913–923 (1996).
- 10.1007/s004010050816 · DOI
- 10.1016/0197-4580(96)00005-X · DOI
- 10.1148/radiology.178.1.1984287 · DOI
- 10.1097/00005072-199805000-00001 · DOI · Paper page
- 10.1006/exnr.1998.6919 · DOI · Paper page
- 10.1093/brain/117.4.747 · DOI
- 10.1001/archpsyc.1992.01820030027004 · DOI · Paper page
- 10.1001/archpsyc.55.6.540 · DOI
- A Pfefferbaum, L Marsh Clin Neurosci 3, 105–111 (1995).
- 10.1001/archpsyc.56.2.142 · DOI
- J R Meyer, S Roychowdhury, E J Russell, C Callahan, D Gitelman, M M Mesulam Am J Neuroradiol 17, 1699–1706 (1996).
- 10.1162/jocn.1993.5.2.162 · DOI · Paper page
- 10.1006/nimg.1998.0395 · DOI · Paper page
- 10.1006/nimg.1998.0396 · DOI · Paper page
- Fischl B. Liu A. & Dale A. M. (1999) IEEE Trans. Med. Imaging in press.
- 10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4 · DOI · Paper page
- 10.1007/BF01908877 · DOI · Paper page
- D MacDonald Ph.D. thesis (McGill University, Montreal, 1998).
- 10.1109/42.544496 · DOI
- 10.1007/BF00133570 · DOI · Paper page
- 10.1162/jocn.1991.3.1.59 · DOI · Paper page
- 10.1109/83.536892 · DOI · Paper page
- 10.1109/42.511745 · DOI · Paper page
- 10.1016/S1361-8415(96)80007-7 · DOI · Paper page
- J A Sethian Level Set Methods. Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge Univ. Press, Cambridge, U.K., 1996).
- 10.4310/jdg/1214444092 · DOI · Paper page
- W H Press, S A Teukolsky, W T Vetterling, B P Flannery Numerical Recipes inc (Cambridge Univ. Press, 2nd. Ed., Cambridge, U.K., 1994).
- 10.1080/10867651.1997.10487472 · DOI · Paper page
- D A Sholl The Organization of the Cerebral Cortex (Wiley, New York, 1956).
- J Talairach, P Tournoux Co-Planar Stereotaxic Atlas of the Human Brain (Thieme, New York, 1988).
Cited by
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Self-citationFischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.021 · Cited by 9,526
Self-citationA reproducible evaluation of ANTs similarity metric performance in brain image registration
Avants, B. B., Tustison, N. J., Song, G., Cook, P. A., Klein, A., & Gee, J. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.025 · Cited by 4,796
Within-subject template estimation for unbiased longitudinal image analysis
Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.084 · Cited by 2,356
Self-citationThinning of the Cerebral Cortex in Aging
Salat, D. H. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh032 · Cited by 1,851
Metadata
- Authors
- Fischl, B., & Dale, A. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2000-09-12
- Volume
- 97
- Issue
- 20
- Pages
- 11050-11055
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2110208125
- Cited by
- 5,818
- References
- 5
- FWCI
- 18.85
- Type
- journal article
- Language
- en
- Open access
- green
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