Biomedical Engineering Reference
In-Depth Information
[90] Laine, A. F., Huda, W., Chen, D., and Harris, J. G., Local enhancement
of masses using continuous scale representations, J. Math. Imaging
Vis., Vol. 7, No. 1, 1997.
[91] Laine, A., and Zong, X., Border indentification of echocardiograms via
multi-scale edge detection and shape modeling, In: IEEE International
Conference on Image Processing, Lausanne, Switzerland, pp. 287-290,
1996.
[92] Koren, I., Laine, A. F., Fan, J., and Taylor, F. J., Edge detection in
echocardiographic image sequences by 3-D multiscale analysis, IEEE
International Conference on Image Processing, Vol. 1, No. 1, pp. 288-
292, 1994.
[93] Dima, A., Scholz, M., and Obermayer, K., Automatic segmentation and
skeletonization of neurons from confocal microscopy images based
on the 3-D wavelet transform, IEEE Trans. Image Process., Vol. 11,
No. 7, pp. 790-801, 2002.
[94] Wilson, R., Calway, A., and Pearson, R., A generalized wavelet trans-
form for Fourier analysis: The multiresolution Fourier transform and
its application to image and audio signal analysis, IEEE Trans. Inf.
Theory, Vol. 38, No. 2, pp. 674-690, 1992.
[95] Yoshida, H., Katsuragawa, S., Amit, Y., and Doi, K., Wavelet snake
for classification of nodules and false positives in digital chest radio-
graphs, In: IEEE EMBS Annual Conference, Chicago, IL, pp. 509-512,
1997.
[96] deRivaz, P. and Kingsbury, N., Fast Segmentation using level set curves
of complex wavelet surfaces, In: IEEE International Conference on
Image Processing, Vol. 3, pp. 29-32, 2000.
[97] Wu, H., Liu, J., and Chui, C., A wavelet frame based image force model
for active contouring algorithms, IEEE Trans. Image Process., Vol. 9,
No. 11, pp. 1983-1988, 2000.
[98] Sun, H., Haynor, D., and Kim, Y., Semiautomatic video object segmen-
tation using VSnakes, IEEE Trans. Circuits Syst. Video Technol., Vol.
13, No. 1, pp. 75-82, 2003.
