A threestepped coordinated level set segmentation method for identifying atherosclerotic plaques on MR-images

Communications in Numerical Methods in Engineering

Volumn 25, Issue 6, 2009, Pages 615-638

  Gloger, Oliver ^a,b   Ehrhardt, Matthias ^a,c   Dietrich, Thore ^a,d   Hellwich, Olaf ^a   Graf, Kristof ^a,d   Nagel, Eike ^a,e  

^a TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

^b UNIVERSITY OF GREIFSWALD   (Germany)

^c WEIERSTRASS INSTITUTE FOR APPLIED ANALYSIS AND STOCHASTICS   (Germany)

^d DEUTSCHES HERZZENTRUM BERLIN   (Germany)

^e KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Active contours; Anisotropic diffusion; Atherosclerotic plaques; Canny edges; Level set segmentation; Medical image segmentation

Indexed keywords

ACTIVE CONTOURS; ANISOTROPIC DIFFUSION; ATHEROSCLEROTIC PLAQUES; CANNY EDGES; LEVEL SET SEGMENTATION; MEDICAL IMAGE SEGMENTATION;

DIFFUSION; DIGITAL IMAGE STORAGE; EDGE DETECTION; IMAGE SEGMENTATION; OBJECT RECOGNITION; OPTICAL ANISOTROPY;

LEVEL MEASUREMENT;

EID: 68749100882     PISSN: 10698299     EISSN: 10990887     Source Type: Journal    
DOI: 10.1002/cnm.1213     Document Type: Article

References (37)

1. Liu F, Xu D, Ferguson MS, Chu B, Saam T, Takaya N, Hatsukami TS, Yuan C, Kerwin WS. Automated in vivo segmentation of carotid plaque MRI with morphology-enhanced probability maps. Magnetic Resonance in Medicine 2005; 55(3):659-668.
2. Kim WY, Astrup AS, Stuber S, Tarnow L, Falk E, Botnar RM, Simonsen C, Pietraszek L, Hansen PR, Manning WJ, Andersen NT, Parving HH. Subclinical coronary and aortic atherosclerosis detected by magnetic resonance imaging in type 1 diabetes with and without diabetic nephropathy. Journal of the American Heart Association 2007; 115(2):228-235.
3. Spuentrup E, Katoh M, Stuber M, Botnar RM, Schäffter T, Bücker A, Günther RW. Coronary MR imaging using free-breathing 3D steady-state free precession with radial k-space sampling. Fortschr Röntgenstr 2003; 175:1330-1334.
4. Spuentrup E, Ruebben A, Mahnken A, Stuber M, Kölker C, Trung HN, Günther RW, Buecker A. Artifact-free coronary magnetic resonance angiography and coronary vessel wall imaging in the presence of a new, metallic, coronary magnetic resonance imaging stent. Journal of the American Heart Association 2005; 111:1019-1026.
5. Jahnke C, Nehrke K, Paetsch I, Schnackenburg B, Gebker R, Fleck E, Nagel E. Improved bulk myocardial motion suppression for navigator-gated coronary magnetic resonance imaging. Journal of Magnetic Resonance Imaging 2007; 26(3):780-786.
6. Langreck H, Schnackenburg B, Nehrke K, Boernert P, Wahl A, Paetsch I, Bornstedt A, Fleck E, Nagel E. MR coronary artery imaging with 3D motion adapted gating (MAG) in comparison to a standard prospective navigator technique. Journal of Cardiovascular Magnetic Resonance 2005; 7(5):793-797.
7. Briley-Saebo KC, Mulder WJ, Mani V, Hyafil F, Amirbekian V, Aguinaldo JG, Fisher EA, Fayad ZA. Magnetic resonance imaging of vulnerable atherosclerotic plaques: current imaging strategies and molecular imaging probes. Journal of Magnetic Resonance Imaging 2007; 26(3):460-479.
8. Frias JC, Williams KJ, Fisher EA, Fayad ZA. Recombinant HDL-like nanoparticles: a specific contrast agent for MRI of atherosclerotic plaques. Journal of the American Chemical Society 2004; 126(50):16316-16317.
9. Gloger O, Jaeger M, Nagel E, Hellwich O. Hierarchical scale space pre-segmentation based on attraction areas for MR-images from atherosclerosis-plaque. Proceedings of International Workshop on Image Analysis in the Life Sciences Theory and Applications (Linz), 2007; 22.
10. Kass M, Witkin A, Terzopoulos D. Snakes: active contour models. International Journal of Computer Vision 1988; 1:321-331.
11. Cohen LD, Cohen I. Finite element methods for active contour models and balloons for 2D and 3D images. IEEE Transactions on Pattern Analysis and Machine Intelligence 1993; 15(11):1131-1147.
12. Davatzikos CA, Prince JL. An active contour model for mapping the cortex. IEEE Transactions on Medical Imaging 1995; 14(1):65-80.
13. Desbleds Mansard C, Canet Soulas EP, Anwander A, Chaabane L, Neyran B, Serfaty JM, Magnin IE, Douek PC, Orkisz M. Quantification of multi-contrast vascular MR Images with the NLSnake, an active contour model: in vitro validation and in vivo evaluation. Magnetic Resonance in Medicine 2004; 51(2):370-379.
14. Rougon N, Prêteux F. Directional adaptive deformable models for segmentation with application to 2D and 3D medical images. Medical Imaging 93: Image Processing; Proceedings of the SPIE 1898. SPIE: Bellingham, WA, 1993; 93-207.
15. Singh A, von Kurowski L, Chiu MY. Cardiac MR image segmentation using deformable models. Biomedical Image Processing and Biomedical Visualization; Proceedings of the SPIE 1905. SPIE: Bellingham, WA, 1993; 8-28.
16. Xu C, Prince JL. Gradient vector flow: a new external force for snakes. IEEE Proceeding Conference on Computer Vision and Pattern Recognition, 1997; 66-71.
17. Caselles V, Kimmel R, Sapiro G. Geodesic active contours. International Journal of Computer Vision 1997; 22(1):61-79.
18. Rousson M, Deriche R. A variational framework for active and adaptive segmentation of vector valued images. Proceedings of the IEEE Workshop on Motion and Video Computing, Orlando, FL, December 2002.
19. Chan T, Vese L. Active contours without edges. IEEE Transactions on Image Processing 2001; 10(2):266-277.
20. Chan T, Vese L. A multiphase level set framework for image segmentation using the mumford and shah model. International Journal of Computer Vision 2002; V50(3):271-293.
21. Sum KW, Paul YS. A novel active contour model using local and global statistics for vessel extraction. IEEE Engineering in Medicine and Biology Society, EMBS 06, 28th Annual International Conference of the IEEE, New York, U.S.A., 2006; 3126-3129.
22. Lankton S, Nain D, Yezzi A, Tannenbaum A. Hybrid geodesic region-based curve evolutions for image segmentation. In Medical Imaging 2007: Physics of Medical Imaging, Hsieh J, Flynn MJ (eds). Proceedings of the SPIE 6510. 2007; 65104U.
23. Jahnke C, Dietrich T, Paetsch I, Koehler U, Preetz K, Schnackenburg B, Fleck E, Graf K, Nagel E. Experimental evaluation of the detectability of submillimeter atherosclerotic lesions in ex vivo human iliac arteries with ultrahigh-field (7.0 T) magnetic resonance imaging. International Journal of Cardiovascular Imaging 2006; 23(4):519-527.
24. Perona P, Malik J. Scale space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence 1990; 12:629-639.
25. Wei GW. Generalized Perona-Malik equation for image restoration. IEEE Signal Processing Letters 1999; 6:165-167.
26. Whitaker RT, Xue X. Variable-conductance, level-set curvature for image processing. IEEE International Conference on Image Processing, 2001; 142-145.
27. Sapiro G. Vector (self) snakes a geometric framework for color, texture, and multiscale image segmentation. Proceedings IEEE International Conference on Image Processing (ICIP-96), Lausanne, vol. 1, 16-19 September 1996; 817-820.
28. Ibanez L, Schroeder W. The ITK Software Guide. Kitware, Inc., 2005.
29. Dervieux A, Thomasset F. A finite element method for the simulation of a Rayleigh-Taylor instability. In Approximation Methods for Navier-Stokes Problems, Rautman R (ed.). Lecture Notes in Mathematics, vol. 771. Springer: Berlin, 1979; 145-158.
30. Osher S, Sethain JA. Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulation. Journal of Computational Physics 1988; 79:12-49.
31. Osher S, Fedkiw R. Level Set Methods and Dynamic Implicit Surfaces. Springer: Berlin, 2003.
32. Osher S, Paragios N. Geometric Level Set Methods in Imaging, Vision and Graphics. Springer: New York, 2003.
33. Sethian JA. Level Set Methods and Fast Marching Methods. Cambridge University Press: Cambridge, 1999.
34. Malladi R, Sethian J, Vemuri B. Shape modelling with front propagation: a level set approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 1995; 17(2):158-174.
35. Caselles V, Catte F, Coll T, Dibos F. A geometric model for active contours in image processing. Numerische Mathematik 1993; 66:1-31.
36. Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 1986; 8(6):679-698.
37. Qin X, Jiang J, Wang W, Zhang F. Canny operator based level set segmentation algorithm for medical images, bioinformatics and biomedical engineering. First International Conference on Volume, Wuhan, China, 6-8 July 2007; 892-895.