References

1. T. Basar and G. J. Olsder. Dynamic Noncooperative Game Theory. Academic Press, 1982.

2. P. Baxandall and H. Liebeck. Vector Calculus. Oxford University Press, 1986.

3. S. M. Blinkov and 1.1. Glezer. The Human Brain in Figures and Tables: A Quantitative Handbook. Plenum Press, New York, 1968.

4. M. Bomans, K. Hohne, U. Tiede, and M. Riemer. 3-D segmentation of MR images of the head for 3-D display. IEEE Trans. Med. Imaging, 9(2):177-183, 1990.

5. M. E. Brummer, R. M. Mersereau, R. L. Eisner, and R. Lewine. Automatic detection of brain contours in MRI data sets. In A. Colchester and D. Hawkes, editors, Information Proc. Med. Imaging, pages 188-204. Springer-Verlag, Berlin, 1991.

6. A. Chakraborty and J. S. Duncan. Game theoretic integration for image segmentation. IEEE Trans. Pattern Anal. Machine Intell, 21(1):12-30, 1999.

7. A. Chakraborty, L. H. Staib, and J. S. Duncan. Deformable boundary finding in medical images by integrating gradient and region information. IEEE Trans. Med. Imaging, 15(6):859-870, 1996.

8. H. E. Cline, W. E. Lorensen, R. Kikinis, and F. Jolesz. Three-dimensional segmentation of MR images of the head using probability and connectivity. J Comp. Assisted Tomogr., 14(6):1037-1045, 1990.

9. L. D. Cohen and I. Cohen. Finite element methods for active contour models and balloons for 2D and 3D images. IEEE Trans. Pattern Anal. Machine Intell., 15(11):1131-1147, 1993.

10. D. Collins, A. Evans, C. Holmes, and T. Peters. Automatic 3D segmentation of neuroanatomical structures from MRI. In Y. Bizais, C. Barillot, and R. Di Paola, editors, Information Proc. Med. Imaging, pages 139-152. Kluwer, Dordrecht, 1995.

11. D. Collins, T. Peters, W. Dai, and A. Evans. Model based segmentation of individual brain structures from MRI data. In R. A. Robb, editor, Visualization Biomed. Comp. 1992, Proc. SPIE 1808, pages 10-23, 1992.

12. T. Cootes, A. Hill, C. Taylor, and J. Haslam. The use of active shape models for locating structures in medical images. In H. H. Barrett and A. F. Gmitro, editors, Information Proc. Med. Imaging, pages 33-47. LNCS 687, Springer, Berlin, 1993.

13. C. Davatzikos and R. N. Bryan. Using a deformable surface model to obtain a shape representation of cortex. IEEE Trans. Med. Imaging, 15(6):785-795, 1996.

14. J. Declerck, G. Subsol, J. Thirion, and N. Ayache. Automatic retrieval of anatomical structures in 3D medical images. In N. Ayache, editor, Comp. Vision, Virtual Reality and Robotics in Med. (CVRMed '95, LNCS 905), pages 153162. Springer, Berlin, 1995.

15. D. C. Van Essen and H. A. Drury. Structural and functional analyses of human cerebral cortex using a surface-based atlas. J. Neuroscience, 17:7079-7102, 1997.

16. D. Geman and S. Geman. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intell., 6(6):721-741, 1984.

17. K. H. Hohne and W. A. Hanson. Interactive 3D segmentation of MRI and CT volumes using morphological operations. J. Comp. Assisted Tomogr., 16(2):285-294, 1992.

18. M. Jouandet, M. Tramo, D. Herron, A. Hermann, W. Loftus, J. Bazell, and M. Gazzaniga. Brainprints: Computer-generated two-dimensional maps of the human cerebral cortex in vivo. J. Cognitive Neuroscience, 1(1):88-117, 1989.

19. T. Kapur, W. Grimson, W. Wells, and R. Kikinis. Segmentation of brain tissue from magnetic resonance images. Med. Image. Anal., 1(2):109-128, 1996.

20. M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models. Int. J. Computer Vision, 1(4):321—331,1988.

21. J. J. Koenderink and A. J. van Doorn. Surface shape and curvature scales. Image and Vision Computing, 10(8):557— 565, October 1992.

22. R. K.-S. Kwan, A. C. Evans, and G. B. Pike. An extensible MRI simulator for post-processing evaluation. In K. Hohne, editor, Visualization Biomed. Computing 1996 (LNCS 1131), pages 135—140, Springer, Berlin, 1996.

23. R. Leahy, T. Hebert, and R. Lee. Applications of Markov random fields in medical imaging. In Information Proc. Med. Imaging, pages 1—14. Wiley-Liss Inc., New York, 1991.

24. D. MacDonald, D. Avis, and A. C. Evans. Proximity constraints in deformable models for cortical surface identification. In Medical Image Computing and ComputerAssisted Intervention (LNCS 1496), pages 650—659. Springer, Berlin, 1998.

25. R. Malladi, R. Kimmel, D. Adalsteinsson, G. Sapiro, V. Caselles and J. A. Sethian. A geometric approach to segmentation and analysis of 3D medical images. In Proc. Workshop Math. Meth. Biomed. Image Anal., pages 244— 252. IEEE Comp. Soc., Los Alamitos, 1996.

26. R. Malladi, J. Sethian and B. Vemuri. Shape modeling with front propagation: A level set approach. IEEE Trans. Pattern Anal. Machine Intell., 17(2):158—175, 1995.

27. B. Manjunath and R. Chellappa. Unsupervised texture segmentation using Markov random field models. IEEE Trans. Pattern Anal. Machine Intell., 13:478—482, 1991.

28. McConnell Brain Imaging Center, Montreal Neurological Institute (MNI), Montreal, Quebec. Brainweb: http:// www.bic.mni.mcgill.ca/brainweb/.

29. G. Owen. Game Theory. Academic Press, New York, 1982.

30. F. Poupon, J. Mangin, D. Hasbroun, C. Poupon, I. Magnin and V. Frouin. Multi-object deformable templates dedicated to the segmentation of brain deep structures. In Medical Image Computing and Computer-Assisted Intervention (LNCS 1496), pages 1134—1143. Springer, Berlin, 1998.

31. J. V. Rambo, X. Zeng, R. T. Schultz, L. Win, L. H. Staib and J. S. Duncan. Platform for visualization and measurement of gray matter volume and surface area within discrete cortical regions from MR images. In Int. Conf. Func. Mapping Human Brain, page S795, 1998.

32. J. A. Sethian. Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Science. Cambridge University Press, 1996.

33. L. H. Staib, A. Chakraborty and J. S. Duncan. An integrated approach for locating neuroanatomical structure from MRI. Int. J. Patt. Recog. Art. Intell., 11(8): 1247— 1269, 1997. (Special Issue on MR Brain Image Analysis.)

34. L. H. Staib and J. S. Duncan. Boundary finding with parametrically deformable models. IEEE Trans. Pattern Anal. Machine Intell, 14(11):1061—1075, 1992.

35. L. H. Staib and J. S. Duncan. Model-based deformable surface finding for medical images. IEEE Trans. Med. Imaging, 15(5):720-731, 1996.

36. G. Szekely, A. Kelemen, C. Brechbüler and G. Gerig. Segmentation of 3D objects from MRI volume data using constrained elastic deformations of flexible Fourier surface models. In N. Ayache, editor, Comp. Vision, Virtual Reality and Robotics in Med. (CVRMed '95, LNCS 905), pages 495505. Springer, Berlin, 1995.

37. P. C. Teo, G. Sapiro and B. A. Wandell. Creating connected representations of cortical gray matter for functional MRI visualization. IEEE Trans. Med. Imaging, 16(6):852-863, 1997.

38. P. Thompson, C. Schwartz and A. Toga. High resolution random mesh algorithms for creating a probabilistic 3D surface atlas of the human brain. NeuroImage, 3:19-34, 1996.

39. B. Vemuri, A. Radisavljevic and C. Leonard. Multiresolution stochastic 3D shape models for image segmentation. In H. H. Barrett and A. F. Gmitro, editors, Information Proc. Med. Imaging, pages 62-76. LNCS 687, Springer, Berlin, 1993.

40. Y. Wang and L. H. Staib. Boundary finding with correspondence using statistical shape models. In Computer Vision and Pattern Recognition, pages 338-345. IEEE Comp. Soc., Los Alamitos, 1998.

41. W. M. Wells, W. Grimson, R. Kikinis and F. A. Jolesz. Statistical intensity correction and segmentation of MRI data. In R. A. Robb, editor, Visualization Biomed. Comp. 1994, Proc. SPIE 2359, pages 148-159, 1994.

42. C. Xu, D. L. Pham, M. E. Rettmann, D. N. Yu and J. L. Prince. Reconstruction of the human cerebral cortex from magnetic resonance images. IEEE Trans. Med. Imaging, 18(6):467-480, 1999.

43. X. Zeng, L. H. Staib, R. T. Schultz and J. S. Duncan. Segmentation and measurement of the cortex from 3D MR images. In Medical Image Computing and ComputerAssisted Intervention (LNCS 1496), pages 519-530. Springer, Berlin, 1998.

44. X. Zeng, L. H. Staib, R. T. Schultz and J. S. Duncan. Volumetric layer segmentation using coupled surfaces propagation. In Computer Vision and Pattern Recognition, pages 708-715. IEEE Comp. Soc., Los Alamitos, 1998.

45. X. Zeng, L. H. Staib, R. T. Schultz and J. S. Duncan. Segmentation and measurement of the cortex from 3D MR images using coupled surfaces propagation. IEEE Trans. Med. Imaging, 18(10), 1999.

46. X. Zeng, L. H. Staib, R. T. Schultz, H. Tagare, L. Win and J. S. Duncan. A new approach to 3D sulcal ribbon finding from MR images. In Medical Image Computing and Computer-Assisted Intervention (LNCS 1679), pages 148157. Springer, Berlin, 1999.

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