Left-ventricle myocardium segmentation using a coupled level-set with a priori knowledge

Computerized Medical Imaging and Graphics

Volumn 30, Issue 4, 2006, Pages 255-262

  Lynch, M ^a   Ghita, O ^a   Whelan, P F ^a  

^a DUBLIN CITY UNIVERSITY   (Ireland)

Author keywords

A priori knowledge; Cardiac; Coupled; Left ventricle; Level set; Segmentation

Indexed keywords

A PRIORI KNOWLEDGE; CARDIAC; COUPLED; LEFT-VENTRICLES; LEVEL-SET; SEGMENTATION;

CARDIOVASCULAR SYSTEM; DATA REDUCTION; IMAGE SEGMENTATION; MATHEMATICAL MODELS; PROBABILISTIC LOGICS; ROBUSTNESS (CONTROL SYSTEMS);

MEDICAL IMAGING;

ARTICLE; ENDOCARDIUM; EPICARDIUM; HEART LEFT VENTRICLE; HEART MUSCLE; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROBABILITY; QUANTITATIVE ANALYSIS;

HEART VENTRICLES; HUMANS; IMAGING, THREE-DIMENSIONAL; PROBABILITY;

EID: 33746192504     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2006.03.009     Document Type: Article

References (28)

1. Lelieveldt B.P.F., van der Geest R.J., Lamb H.J., Kayser H.W.M., and Reiber J.H.C. Automated observer-independent acquisition of cardiac short-axis MR images: a pilot study. Radiology 221 2 (2001) 537-542
2. Pednekar A, Kakadiaris IA, Kurkure U. Adaptive fuzzy connectedness-based medical image segmentation. In: Indian Conference on Computer Vision, Graphics and Image Processing 2002. Ahmedabad, India, December 2002.
3. Kass M., Witkin A., and Terzopoulos D. Snakes: active contour models. Int J Comput Vis 1 4 (1988) 321-331
4. Kaus M., von Berg J., Niessen W.J., and Pekar V. Automated segmentation of the left ventricle in cardiac mri. Med Image Anal 8 (2004) 245-254
5. Cootes T.F., Edwards G.J., and Taylor C.J. Active appearance models. Lect Notes Comput Sci 1407 (1998) 484-498
6. Hamarneh G., and Gustavsson T. Combining snakes and active appearance shape models for segmenting the human left ventricle in echocardiographic images. IEEE Comput Cardiol 27 (2000) 115-118
7. Rogers M, Graham J. Robust active shape model search. In: Proceedings of the 7th European Conference on Computer Vision, May 2002, p. 517-30.
8. Stegmann MB, Larsson HBW. Motion-compensation of cardiac perfusion MRI using a statistical texture ensemble. In: Functional Imaging and Modelling of the Heart (FIMH'03), Lyon, France, June 2003, p. 151-61.
9. Mitchell S.C., Lelieveldt B.P.F., van der Geest R.J., Bosch H.G., Reiber J.H.C., and Sonka M. Multistage hybrid acive appearance model matching: segmentation of left ventricles in cardiac MR images. IEEE Trans Med Imaging 20 5 (2001) 415-423
10. Bosch J.G., Mitchell S.C., Lelieveldt B.P.F., Nijland F., Kamp O., Sonka M., and Reiber J.H.C. Automatic segmentation of echocardiographic sequences by active appearance motion models. IEEE Trans Med Imaging 21 11 (2002)
11. Osher S., and Sethian J.A. Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations. J. Comput Phys 79 (1988) 12-49
12. Sethian JA. An analysis of flame propagation. Ph.D. thesis, University of California, Department of Mathematics, University of California, Berkeley, CA, USA, 1982.
13. Sethian JA. A marching level set method for monotonically advancing fronts. In: Proceedings of the National Academy of Sciences, vol. 93, 1996.
14. Caselles V., Kimmel R., and Sapiro G. Geodesic active contours. Int J Comput Vis 22 1 (1997) 61-79
15. Caselles V., Catté F., Coll T., and Dibos F. A geometric model for active contours in image processing. Numerische Mathematik 66 1 (1993) 1-31
16. Malladi R., Sethian J.A., and Vermuri B.C. Shape modeling with front propagation: a level set approach. IEEE Trans Pattern Anal Machine Intell 17 (1995) 158-175
17. Malladi R, Sethian JA. Level set methods for curvature flow, image enhancement, and shape recovery in medical images. In: Proceedings of Conference on Visualization and Mathematics, Berlin, Germany, June 1997.
18. Niessen W.J., ter Haar Romeny B.M., and Viergever M.A. Geodesic deformable models for medical image analysis. Trans Med Imaging 17 4 (1998) 634-642
19. Zeng X, Staib LH, Schultz RT, Duncan JS. Segmentation and measurement of the cortex from 3D MR images. In: Medical Image Computing and Computer Asssisted Intervention, MICCAI, October 1998.
20. Paragios N. A variational approach for the segmentation of the left ventricle in cardiac image analysis. Int J Comput Vis 50 3 (2002) 345-362
21. Leventon ME, Grimson WEL, Faugeras O. Statistical shape influence in geodesic active contours. In: Proceedings of Computer Vision and Pattern Recognition, 2000.
22. Chan T., and Vese L. Active contours without edges. IEEE Trans Image Process 10 2 (2001) 266-277
23. Mumford D., and Shah J. Optimal approximations by piecewise smooth functions and associated variational problems. Comm Pure Appl Math 42 5 (1989) 577-585
24. Paragios N. A level set approach for shape-driven segmentation and tracking of the left ventricle. IEEE Trans Med Imaging 22 6 (2003) 773-776
25. Laidlaw D.H., Fleischer K.W., and Barr A.H. Partial-volume bayesian classification of material mixtures in mr volume data using voxel histograms. IEEE Trans Med Imaging 17 1 (1998) 74-86
26. Khalighi M, Soltanian-Zadeh H, Lucas C. Unsupervised mri segmentation with spatial connectivity. In: Proceedings of the SPIE International Symposium on Medical Imaging, February 2002.
27. Bland J.M., and Altman D.G. Statiscal methods for assessing agreement between two methods of clinical measurements. Lancet 1 8476 (1986) 307-310
28. Chen Q, Zhou Z, Qu Y, Heng PA, Xia D. Level set based auto segmentation of the tagged left ventricle mr images. In: Proceedings of Medicine Meets Virtual Reality 12, vol. 12, Newport Beach, CA, USA, 2004, p. 63-65.