Biomedical Engineering Reference
In-Depth Information
8.
NOTES
1.
A preliminary version of this work was presented in [16].
9.
REFERENCES
1. Dervieux A, Thomasset F. 1979. A finite element method for the simulation of Rayleigh-
Taylor instability. In
Approximation methods for Navier-Stokes problems
, pp. 145-158. Ed R
Rautmann. Berlin: Springer.
2. Osher SJ, Sethian JA. 1988. Front propagation with curvature dependent speed: algorithms
based on Hamilton-Jacobi formulations.
J Comput Phys
79
:12-49.
3. Caselles V, Catte F, Coll T, Dibos F. 1993. A geometric model for active contours in image
processing.
Num Math
66
:1-31.
4. Malladi R, Sethian JA, Vemuri BC. 1994. A topology independent shape modeling scheme.
In
Proceedings of the SPIE conference on geometric methods in computer vision
, Vol. 2031,
pp. 246-258. Bellingham, WA: SPIE.
5. Kichenassamy S, Kumar A, Olver PJ, Tannenbaum A, Yezzi AJ. 1995. Gradient flows and
geometric active contourmodels. In
Proceedings of the fifth international conference computer
vision (ICCV'95)
, pp. 810-815. Washington, DC: IEEE Computer Society.
6. Leventon M, Grimson W, Faugeras O. 2000. Statistical shape influence in geodesic active
contours. In
Proceedings of the IEEE international conference on computer vision and pattern
recognition (CVPR)
, Vol. 1, pp. 316-323. Washington, DC: IEEE Computer Society.
7. Tsai A, Yezzi AJ, Willsky AS. 2003. A shape-based approach to the segmentation of medical
imagery using level sets.
IEEE Trans Med Imaging
,
22
(2):137-154.
8. Cremers D, Osher SJ, Soatto S. 2006. Kernel density estimation and intrinsic alignment for
shape priors in level set segmentation.
Int J Comput Vision
.
69
(3):335-351.
9. Rousson M, Paragios N, Deriche R. 2004. Implicit active shape models for 3d segmentation
in MRI imaging. In
Proceedings of the international conference on medical image computing
and computer-assisted intervention (MICCAI 2000)
.
Lecture notes in computer science
, Vol.
2217, pp. 209-216. New York: Springer.
10. Dam EB, Fletcher PT, Pizer S, Tracton G, Rosenman J. 2004. Prostate shape modeling based
on principal geodesic analysis bootstrapping. In
Proceedings of the international conference
on medical image computing and computer-assisted intervention (MICCAI 2003)
.
Lecture
notes in computer science
, Vol. 2217, pp. 1008-1016. New York: Springer.
11. Freedman D, Radke RJ, Zhang T, Jeong Y, Lovelock DM, Chen GT. 2005. Model-based seg-
mentation of medical imagery bymatching distributions.
IEEETransMed Imaging
24
(3):281-
292.
12. Rosenblatt F. 1956. Remarks on some nonparametric estimates of a density function.
Ann
Math Stat
27
:832-837.
13. Silverman BW. 1992.
Density estimation for statistics and data analysis
. London: Chapman
and Hall.
14. Paragios N, Deriche R. 2002. Geodesic active regions and level set methods for supervised
texture segmentation.
Int J Comput Vision
46
(3):223-247.
15. Chan LAVese TF. 2001. Active contours without edges.
IEEE TransMed Imaging
,
10
(2):266-
277.
16. Rousson, M., Cremers, D., 2005. Efficient Kernel Density Estimation of Shape and Intensity
Priors for Level Set Segmentation,
International conference on medical image computing and
computed-assisted intervention (MICCAI 2005)
,
2
: 757-764.
