Segmentation of 3D tubular structures by a PDE-based anisotropic diffusion model

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

Volumn 5862 LNCS, Issue , 2010, Pages 224-241

  Franchini, Elena ^a   Morigi, Serena ^a   Sgallari, Fiorella ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ANISOTROPIC DIFFUSION MODEL; CURVATURE MOTION; DIFFUSION MODEL; DIFFUSION TENSOR; EFFICIENT STRATEGY; FINITE VOLUME SCHEMES; GRADIENT FLOW; INITIAL DISTANCE; ITERATIVE SOLVERS; NON-LINEAR; PDE MODEL; SEMI-IMPLICIT APPROACH; SPACE DISCRETIZATIONS; TUBE GEOMETRY; TUBULAR STRUCTURES; VARIATIONAL FORMULATION;

AIRCRAFT ENGINES; ANISOTROPY; DIFFUSION; EQUATIONS OF MOTION; IMAGE SEGMENTATION; LINEAR SYSTEMS; PARTIAL DIFFERENTIAL EQUATIONS; TENSORS; TUBULAR STEEL STRUCTURES;

THREE DIMENSIONAL;

EID: 77950173998     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-11620-9_15     Document Type: Conference Paper

References (27)

1. Antiga, L., Ene-Iordache, B., Remuzzi, A.: Computational geometry for patient-specific reconstruction and meshing of blood vessels from MR and CT angiography. IEEE Transaction on Medical Imaging 22(5), 674-684 (2003)
2. Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. In: Proc. ICCV 1995, Cambridge, MA, pp. 694-699 (1995)
3. Cohen, L.D., Deschamps, T.: Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging. Computer Methods in Biomechanics and Biomedical Engineering 10(4), 289-305 (2007)
4. Corsaro, S., Mikula, K., Sarti, A., Sgallari, F.: Semi-implicit co-volume method in 3D image segmentation. SIAM Journal on Scientific Computing 28(6), 2248-2265 (2006)
5. Dekanic, K., Loncari, S.: 3D vascular tree segmentation using level set deformable model. In: Proceeding of the 5th International Symposium on image and signal Processing and analysis (2007)
6. Deschamps, T., Schwartz, P., Trebotich, D., Colella, P., Saloner, D., Malladi, R.: Vessel segmentation and blood flow simulation using level set and embedded boundary method. International Congress Series, vol. 1268, pp. 75-80 (2004)
7. Drblikova, O., Mikula, K.: Semi-implicit Diamond-cell Finite volume Scheme for 3D Nonlinear Tensor Diffusion in Coherence Enhancing Image Filtering. In: Eymard, R., Herard, J.M. (eds.) Finite Volumes for Complex Applications V: Problems and Perspectives, ISTE and WILEY, London, pp. 343-350 (2008)
8. Eymard, R., Gallouet, T., Herbin, R.: The finite volume method. In: Ciarlet, P., Lions, J.L. (eds.) Handbook for Numerical Analysis, vol. 7. Elsevier, Amsterdam (2000)
9. Franchini, E., Morigi, S., Sgallari, F.: Composed Segmentation of Tubular Structures by an Anisotropic PDE Model. In: Tai, X.-C., et al. (eds.) SSVM 2009. LNCS, vol. 5567, pp. 75-86. Springer, Heidelberg (2009)
10. Gooya, A., Liao, H., et al.: A variational method for geometric regularization of vascular segmentation in medical images. IEEE Transaction on Image Processing 17(8), 1295-1312 (2008)
11. Handlovi cova, A., Mikula, K., Sgallari, F.: Semi-implicit complementary volume scheme for solving level set like equations in image processing and curve evolution. Numer. Math. 93, 675-695 (2003)
12. Hassan, H., Farag, A.A.: Cerebrovascular segmentation for MRA data using levels set. International Congress Series, vol. 1256, pp. 246-252 (2003)
13. Kirbas, C., Quek, F.: A review of vessel extraction techniques and algorithms. ACM Computing Surveys 36(2), 81-121 (2004)
14. Le Veque, R.: Finite volume methods for hyperbolic problems. Cambridge Texts in Applied Mathematics. Cambridge University Press, Cambridge (2002)
15. Meijering, E., Niessen, W., Weickert, J., Viergever, M.: Diffusion-enhanced visualization and quantification of vascular anomalies in three-dimensional rotational angiography: Results of an in-vitro evaluation. Medical Image Analysis 6(3), 215-233 (2002)
16. Mikula, K., Sarti, A., Sgallari, F.: Co-volume level set method in subjective surface based medical image segmentation. In: Suri, J., et al. (eds.) Handbook of Medical Image Analysis: Segmentation and Registration Models, pp. 583-626. Springer, New York (2005)
17. Osher, S., Fedwik, R.: Level Set Methods and Dynamic Implicit Surfaces. Applied Mathematical Sciences, vol. 53. Springer, New York (2002)
18. Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12, 629-639 (1990)
19. Reichel, L., Ye, Q.: Breakdown-free GMRES for singular systems. SIAM J. Matrix Anal. Appl. 26, 1001-1021 (2005)
20. Saad, Y.: Iterative methods for sparse linear systems. PWS Publ. Comp. (1996)
21. Scherl, H., et al.: Semi automatic level set segmentation and stenosis quatification of internal carotid artery in 3D CTA data sets. Medical Image Analysis 11, 21-34 (2007)
22. Sarti, A., Malladi, R., Sethian, J.A.: Subjective Surfaces: A Geometric Model for Boundary Completion. International Journal of Computer Vision 46(3), 201-221 (2002)
23. Sethian, J.A.: Level Set Methods and Fast Marching Methods. Evolving Interfaces in Computational Geometry. Fluid Mechanics, Computer Vision, and Material Science. Cambridge University Press, Cambridge (1999)
24. Walkington, N.J.: Algorithms for computing motion by mean curvature. SIAM J. Numer. Anal. 33(6), 2215-2238 (1996)
25. Weickert, J.: Coherence-enhancing diffusion of colour images. Image and Vision Computing 17, 201-212 (1999)
26. Weickert, J., Scharr, H.: A scheme for coherence enhancing diffusion filtering with optimized rotation invariance. Journal of Visual Communication and Image Representation 13(1/2), 103-118 (2002)
27. Westin, C.-F., Lorigo, L.M., Faugeras, O.D., Grimson, W.E.L., Dawson, S., Norbash, A., Kikinis, R.: Segmentation by Adaptive Geodesic Active Contours. In: Proceedings of MIC-CAI 2000, Third International Conference on Medical Image Computing and Computer-Assisted Intervention, October 11-14, pp. 266-275 (2000)