A technique for single-channel MR brain tissue segmentation: Application to a pediatric sample

Magnetic Resonance Imaging

Volumn 14, Issue 9, 1996, Pages 1053-1065

  Rajapakse, Jagath C ^a   Giedd, Jay N ^a   DeCarli, Charles ^b   Snell, John W ^c   McLaughlin, Alan ^a   Vauss, Yolanda C ^a   Krain, Amy L ^a   Hamburger, Susan ^a   Rapoport, Judith L ^a  

^a NATIONAL INSTITUTE OF MENTAL HEALTH   (United States)

^b National Institute of Neurological Disorders   (United States)

^c UNIVERSITY OF VIRGINIA   (United States)

Author keywords

Brain imaging; Cerebrospinal fluid; Gray matter; Magnetic resonance imaging; Region growing; White matter

Indexed keywords

ADOLESCENT; ARTICLE; BRAIN SIZE; BRAIN TISSUE; CEREBROSPINAL FLUID; CHILD; FEMALE; GRAY MATTER; HUMAN; HUMAN EXPERIMENT; MALE; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; PEDIATRICS; PHANTOM; PRIORITY JOURNAL; RELIABILITY; TECHNIQUE; WHITE MATTER;

EID: 0030454307     PISSN: 0730725X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0730-725X(96)00113-0     Document Type: Article

References (44)

1. 1. Rajapakse, J.C.; DeCarli, C.; Giedd, J.N.; McLaughlin, A.; Hamburger, S.D.; Rapoport, J.L. Cerebral magnetic resonance image segmentation using data fusion. J. Comput. Assist. Tomogr. 20(2):208-216; 1996.
2. 2. Yakovlev, P.I.; Lecours, A.R. The myelogenetic cycles of regional maturation of the brain. In: A. Minowski (Ed). Regional Development in Brain in Early Life. Oxford: Blackwell Scientific; 1967: pp. 3-69.
3. 3. Cohen, G.; Andreasen, N.C.; Alliger, R.; Arndt, S.; Kuan, J.; Yuh, W.T.C.,; Ehrhardt, J. Segmentation techniques for the classification of brain tissue using magnetic resonance imaging. Psychiatry Res. 45:33-51; 1992.
4. 4. Jernigan, T.L.; Press, G.A.; Hesselink, J.R. Methods for measuring brain morphologic features on magnetic resonance images: validation and normal aging. Arch. Neurology 47:27-32; 1990.
5. 5. Lim, K.O.; Pfefferbaum, A. Segmentation of MR brain images into cerebrospinal fluid spaces, white and gray matter. J. Comput. Assist. Tomogr. 13(4):588-593; 1989.
6. 6. Harris, G.J.; Barta, P.E.; Peng, L.W.; Lee, S.; Brellschnder, P.D.; Shah, A.; Henderer, J.D.; Schlaepfer, T.E.; Pearlson, G.D. MR volume segmentation of gray matter and white matter using manual thresholding: dependence on image brightness. Am. J. Neuroradiol. 15:225-230; 1994.
7. 7. Harris, G.J.; Rhew, E.H.; Noga, T.; Pearison, G.D. User-friendly method for rapid brain and CSF volume calculation using transaxial MR images. Psychiatry Res. 40:61-68; 1991.
8. 8. Raya, S.P. Low-level segmentation of 3-D magnetic resonance brain images - a rule-based system. IEEE Trans. Med. Imag. 9(3):327-337; 1990.
9. 9. Vannier, M.W.; Butterfield, R.L.; Jordan, D.; Murphy, W.A.; Levitt, R.G.; Gado, M. Multispectral analysis of magnetic resonance images. Radiology 154:221-224; 1985.
10. 10. Vannier, M.W.; Pilgram, T.K.; Speidel, T.M.; Neumann, R.L.; Rickman, D.L.; L.D. Schertz. Validation of magnetic resonance imaging multispectral tissue classification. Comput. Med. Imaging Graph. 15(4): 217-223; 1991.
11. 11. Clarke, L.P.; Velthuizen, R.P.; Phuphanich, S.; Schellenberg, J.D.; Arrington, J.A.; Silbiger, M. MRI: stability of three supervised segmentation techniques. Magn. Reson. Imaging 11:95-106; 1993.
12. 12. Liang, Z. Tissue classification and segmentation of MR images. IEEE Eng. Med. Biol. 39:81-85; 1993.
13. 13. Choi, H.S.; Haynor, D.R.; Kim, Y. Partial volume tissue classification of multichannel magnetic resonance images. IEEE Trans. Med. Imaging 10(3)395-407; 1991.
14. 14. Caviness, V.S.; Filipek, P.A.; Kennedy, D.N. Magnetic resonance technology in human brain science: blueprint for a program based upon morphometry. Brain Dev. 11(1):1-11; 1989.
15. 15. Pal, N.R.; Pal, S.K. A review on image segmentation techniques. Pattern Recogn. 26(9):1277-1294; 1993.
16. 16. Morrison, M.; Attikiouzel, Y. An introduction to the segmentation of magnetic resonance medical images. Aust. Comput. J. 26(3):90-98; 1994.
17. 17. Sahoo, P.K.; Soltani, S.; Wong, A.K.C. A survey of thresholding technique. Comput. Vision Graph. Image Proc. 41:233-260; 1988.
18. 18. Kennedy, D.N.; Filipek, P.A.; Caviness, V.S., Jr. Anatomic segmentation and volumetric calculations in nuclear magnetic resonance imaging. IEEE Tran. Med. Imag. 8(1):1-7; 1989.
19. 19. Filipek, P.A.; Kennedy, D.N.; Caviness, V.S., Jr.; Rossnick, S.L.; Spraggins, T.A.; Starewics, P.M. Magnetic resonance imaging-based brain morphometry: development and application to normal subjects. Ann. Neurol. 25(1):61-67; 1989.
20. 20. Filipek, P.A.; Richelme, C.; Kennedy, D.N.; Caviness, V.S., Jr. The young adult human brain: an MRI-based morphometric analysis. Cerebral Cortex 4(4):344-360; 1994.
21. 21. DeCarli, C.; Maisog, J.; Murphy, D.G.M.; Teichberg, D.; Rapoport, S.I.; Horwitz, B. Method for quantification of brain, ventricular and subarachnoid CSF volumes from MR images. J. Comput. Assist. Tomogr. 16(2): 274-284; 1992.
22. 22. Van Meter, J.W. Segmentation and restoration of magnetic resonance images using material mixture models. Ph.D. Dissertation, Dartmouth College, September 1993.
23. 23. Amartur, S.C.; Piraino, D.; Takefuji, Y. Optimization neural networks for the segmentation of magnetic resonance images. IEEE Tran. Med. Imaging 11(2):215-220; 1992.
24. 24. Ozkan, M.; Dawant, B.M.; Maciunas, R.J. Neural network-based segmentation of multi-modal medical images: a comparative and prospective study. IEEE Tran. Med. Imaging 12(3):553-554; 1993.
25. 25. Hall, L.O.; Bensaid, A.M.; Clarke, L.P.; Velthuizen, M.S.; Silbiger, M.S.; Bezdek, J.C. A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain. IEEE Tran. Neural Networks 3(5):672-682; 1992.
26. 26. Brandt, M.E.; Bohan, T.P.; Kramer, L.A.; Fletcher, J.M. Estimation of CSF, white, and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images. Comput. Med. Imaging Graph. 18(1):25-34; 1994.
27. 27. Pappas, T.N. An adaptive clustering algorithm for image segmentation. IEEE Tran. Signal Proc. 40(4):901-914; 1992.
28. 28. Jernigan, T.L.; Tallal, P. Late childhood changes in brain morphology observable with MRI. Dev. Med. Child Neurol. 32(5-6):379-385; 1990.
29. 29. Jernigan, T.L.; Archibald, S.L.; Berhow, M.T.; Sowell, E.R.; Foster, D.S.; Hesselink, J.R. Cerebral structure on MRL Part 1: localization of age-related changes. Biol. Psychiatry 29:55-67; 1991.
30. 30. Jernigan, T.L.; Trauner, D.A.; Hesselink, J.R.; Tallal, P.A. Maturation of human cerebrum observed in vivo during adolescence. Brain 114:2037-2049; 1991.
31. 31. Lim, K.O.; Zipursky, R.B.; Watts, M.C.; Pfefferbaum, A. Decreased gray matter in normal aging: an in vivo magnetic resonance study. J. Gerontol. 47(1):B26-30; 1992.
32. 32. Pfefferbaum, A.; Mathalon, D.H.; Sullivan, E.V.; Rawles, J.M.; Zipursky, R.B.; Lim, K.O. A quantitative magnetic resonances imaging study of changes in brain morphology from infancy to late adulthood. Arch. Neurol. 51:874-887; 1994.
33. 33. Giedd, J.N.; Snell, J.W.; Lange, N.; Rajapakse, J.C.; Kozuch, P.; Casey, B.J.; Kaysen, D.; King, A.C.; Hamburger, S.D.; Rapoport, J.L. Quantitative magnetic resonance imaging of human brain development: ages 5-18. Cerebral Cortex 6:551-560, 1996.
34. 34. Perona, P.; Malik, J. Scale space and edge detection using anisotropic diffusion. IEEE Tran. Pattern Analy. Machine Intell. 12(7):629-639; 1990.
35. 35. Gerig, G.; Kubler, O.; Kikinis, R.; Jolesz, F.A. Nonlinear anisotropic filtering of MRI data. IEEE Tran. Med. Imaging 11(2):221-232; 1992.
36. 36. Snell, J.W.; Merickel, M.; Onega, J.; Goble, J.; Brookeman, J.; Kassell, N. Model-based boundary estimation of complex objects using hierarchical active surface templates. Pattern Recognition 28(10):1599-1609; 1995.
37. 37. Talairach, J.; Tournoux, P. (Eds). Co-Planar Stereotaxic Atlas of the Human Brain. New York: Thieme Medical Publishers, Inc.; 1988.
38. 38. Duda, R.O.; Hart, P.R. Pattern Classification and Scene Analysis. New York: John Willey and Sons; 1973.
39. 39. Chang, H.; Fitzpatrick, J.M. A technique for accurate magnetic resonance imaging in the presence of field inhomogeneities. IEEE Tran. Med. Imaging 31(3) :319-329; 1992.
40. 40. DeCarli, C.; Murphy, D.G.M.; Teichberg, D.; Campbell, G.; Sobering, G.S. Local histogram correction of MRI spatially dependent image pixel intensity nonuniformity. JMRI 6:519-528; 1996.
41. 41. Madsen, E.L.; Fullerton, G.D. Prospective tissue-mimicking materials for use in NMR imaging phantoms. Magn. Reson. Imaging 1:135-141; 1982.
42. 42. Bulte, J.W.; Douglas, T.; Mann, S.; Grankel, R.B.; Moskowitz, B.M.; Brooks, R.A.; Baumgarner, C.D.; Vymazal, J.; Strub, M.; Frank, J.A. Magnetoferritin characterization of a novel superparamagnetic MR contrast agent. Magn. Reson. Imaging 4:497-505; 1994.
43. 43. Rademache, J.; Galaburda, A.M.; Kennedy, D.N.; Filipek, P.A.; Caviness, V.S. Human cerebral cortex: localization, parcellation, and morphometry with magnetic resonance imaging. J. Cognitive Neurosci. 4(4):352-374; 1992.
44. 44. Goldman-Rakic, P.S. The frontal lobes: uncharted provinces of the brain. Trends Neurosci. 7:425-429; 1984.