Biomedical Engineering Reference
In-Depth Information
[74] Williams, C. K. I., Revow, M., and Hinton, G. E., Instantiating de-
formable models with a neural net, Comput. Vis. Image Underst., Vol.
68, No.1, pp. 120-126, 1997.
[75] Niessen, W.J., ter Haar Romery, B.M., and Viergever, M. A., Geodesic de-
formable models for medical image analysis, IEEE Trans. Med. Imag-
ing, Vol. 17, No. 4, pp. 634-641, 1998.
[76] Xu, C., Pham, D., Rettmann, M., Yu, D., and Prince, J., Reconstruction
of the human cerebral cortex from magnetic resonance images, IEEE
Trans. Med. Imaging, Vol. 18, No. 6, pp. 467-480, 1999.
[77] Xu, C. and Prince, J. L., Snakes, shapes, and gradient vector flow, IEEE
Trans. Image Process., Vol. 7, No. 3, pp. 359-369, 1998.
[78] Xu, C. and Prince, J. L., Global optimality of gradient vector flow,
In: Proc. of the Conference on Information Sciences and Systems,
Princeton University, March 2000.
[79] Xu, Gang, Segawa, E., and Tsuji, S., Robust active contours with in-
sensitive parameters, Pattern Recognit., Vol. 27, No. 7, pp. 879-884,
1994.
