Highly accurate segmentation of brain tissue and subcortical gray matter from newborn MRI

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4190 LNCS - I, Issue , 2006, Pages 199-206

  Weisenfeld, Neil I ^a,b   Mewes, Andrea U J ^a   Warfield, Simon K ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

^b BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BRAIN; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING;

BAYESIAN APPROACH; BRAIN TISSUE; STAPLE ALGORITHM;

TISSUE;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NERVE CELL; NEWBORN; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFANT, NEWBORN; MAGNETIC RESONANCE IMAGING; NEURONS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 33750246312     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11866565_25     Document Type: Conference Paper

References (21)

1. Martin, J.A., Hamilton, B.E., Sutton, P.D., Ventura, S.J., Menakcker, F., Munson, M.L.: Births: Final data for 2003. National Vital Statistics Reports 54(2) (2005)
2. Warfield, S.K., Zou, K.H., Wells, W.M.: Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Trans. Med. Imag. 23 (2004) 903-921
3. Viola, P.A.: Alignment by maximization of mutual information. PhD thesis, MIT, Cambridge, MA, USA (1995)
4. Mangin, J.F.: Entropy minimization for automatic correction of intensity nonuniformity. In: Math. Methods in Biomed. Imag. Anal., Los Alamitos, California, IEEE Computer Society (2000) 162-169
5. Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Pat. Anal. Mach. Intel. 12 (1990) 629-639
6. Gerig, G., Kubler, O., Kikinis, R., Jolesz, F.: Nonlinear anistropic filtering of MRI data. IEEE Trans. Med. Imag. 2 (1992) 221-232
7. Yoo, T.S.: Insight into Images. A. K. Peters (2004)
8. Warfield, S.K., Kaus, M., Jolesz, F.A., Kikinis, R.: Adaptive, template moderated, spatially varying statistical classification. Medical Image Analysis 4(1) (2000) 43-55
9. Warfield, S.K.: Segmentation of Magnetic Resonance Images of the Brain. PhD thesis, The University of New South Wales, Australia (1997)
10. Weisenfeld, N.L, Mewes, A.U.J., Warfield, S.K.: Segmentation of newborn brain MRI. In: Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging, Piscataway, NJ, IEEE (2006) Conference held April 6-9, 2006, Crystal City, Virginia, USA.
11. Duda, R.O., Hart, P.E.: Pattern Classification and Scence Analysis. John Wiley and Sons, New York, NY, USA (1973)
12. Leemput, K.V., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based tissue classification of MR images of the brain. IEEE Trans. Med. Imag. 18 (1999) 897-908
13. Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26 (1945) 207-302
14. Zijdenbos, A.P., Dawant, B.M., Margolin, R.A., Palmer, A.C.: Morphometric analysis of white matter lesions in MR images: Method and validation. IEEE Trans. Med. Imag. 13(4) (1994) 716-724
15. Wells, W.M., Kikinis, R., Grimson, W.E.L., Jolesz, F.: Adaptive segmentation of MRI data. IEEE Trans. Med. Imag. 15(4) (1996) 429-442
16. Zhang, Y., Brady, M., Smith, S.M.: Segmentation of brain MR images thorough a hidden markov random field model and the expectation maximization algorithm. IEEE Trans. Med. Imag. 20(1) (2002) 45-57
17. Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., Dale, A.M.: Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron 33(3) (2002) 341-355
18. Peterson, B.S., Anderson, A.W., Ehrenkranz, R., Staib, L.H., Tageldin, M., Colson, E., Gore, J.C., Duncan, C.C., Makuch, R., Ment, L.R.: Regional brain volumes and their later neurodevelopmental correlates in term and preterm infants. Pediatrics 111 (2006) 939-948
19. Prastawa, M., Gilmore, J.H., Lin, W., Gerig, G.: Automatic segmentation of MR images of the developing newborn brain. Medical Image Analysis 9 (2005) 457-466
20. Cocosco, C.A., Zijdenbos, A.P., Evans, A.C.: A fully automatic and robust brain MRI tissue classification method. Medical Image Analysis 7 (2003) 513-527
21. Grau, V., Mewes, A.U.J., Raya, M.A., Kikinis, R., Warfield, S.K.: Improved watershed transform for medical image segmentation using prior information. IEEE Trans. Med. Imag. 23(4) (2004) 447-458