An efficient optimization framework for multi-region segmentation based on lagrangian duality

IEEE Transactions on Medical Imaging

Volumn 32, Issue 2, 2013, Pages 178-188

  Ulen, Johannes ^a   Strandmark, Petter ^a   Kahl, Fredrik ^a  

^a LUND UNIVERSITY   (Sweden)

Author keywords

Cardiac segmentation; discrete optimization; image segmentation; lung segmentation

Indexed keywords

CARDIAC SEGMENTATION; DISCRETE OPTIMIZATION; FULL BODY; GEOMETRIC CONSTRAINT; GLOBAL OPTIMIZATION TECHNIQUES; GRAPH CUT; INTENSITY DISTRIBUTION; LAGRANGIAN DUALITY; LEFT VENTRICULAR; LUNG SEGMENTATION; MEDICAL IMAGES; MEMORY EFFICIENT; MULTIREGION MODELS; OPTIMIZATION FRAMEWORK; PAPILLARY MUSCLE; RIGHT VENTRICLE; STATE OF THE ART; X-RAY COMPUTED TOMOGRAPHY;

BIOLOGICAL ORGANS; IMAGE SEGMENTATION; LAGRANGE MULTIPLIERS; MAGNETIC RESONANCE IMAGING;

OPTIMIZATION;

ARTICLE; HEART LEFT VENTRICLE; HEART MUSCLE; HEART PAPILLARY MUSCLE; HEART RIGHT VENTRICLE; IMAGE PROCESSING; MATHEMATICAL MODEL; MULTIREGION IMAGE SEGMENTATION; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCESS DESIGN; PROCESS OPTIMIZATION; WHOLE BODY CT; ALGORITHM; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

MLCS; MLOWN;

EID: 84873282421     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2012.2218117     Document Type: Article

References (41)

1. MICCAI cardiac MR left ventricle segmentation challenge 2009 [Online]. Available: http://smial.sri.utoronto.ca/LV Challenge/Home.html
2. B. Appleton and H. Talbot, "Globally minimal surfaces by continuous maximal flows," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 1, pp. 106-118, Jan. 2006. (Pubitemid 46395308)
3. S.G.Armato, III and W. F. Sensakovic, "Automated lung segmentation for thoracic CT: Impact on computer-aided diagnosis," Acad. Radiol., vol. 11, no. 9, pp. 1011-1021, 2004. (Pubitemid 39220811)
4. A. Blake, P. Kohli, and C. Rother, Eds., Markov Random Fields for Vision and Image Processing. Cambridge, MA: MIT Press, 2011.
5. E. Boros and P. L. Hammer, "Pseudo-boolean optimization," Discrete Appl. Math., vol. 123, pp. 155-225, 2002.
6. E. Boros, P. L. Hammer, and X. Sun, Network flows and minimization of quadratic pseudo-Boolean functions RUTCOR RRR 17-1991, 1991, RUTCOR RRR 17-1991.
7. E. Boros, P. L. Hammer, and G. Tavares, Preprocessing of unconstrained quadratic binary optimization RUTCOR RRR 10-2006, 2006.
8. Y. Boykov and M.-P. Jolly, "Interactive organ segmentation using graph cuts," in Conf. Med. Image Comput. Computer-Assist. Intervent., 2000, pp. 147-175.
9. Y. Boykov and V. Kolmogorov, "Computing geodesics and minimal surfaces via graph cuts," Proc. ICCV, pp. 26-33, 2003.
10. Y. Boykov and V. Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 9, pp. 1124-1137, Sep. 2004.
11. Y. Boykov, O. Veksler, and R. Zabih, "Fast approximate energy minimization via graph cuts," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 11, pp. 1222-1239, Nov. 2001. (Pubitemid 33137959)
12. C. Casta, P. Clarysse, J. Schaerer, and J. Pousin, Evaluation of the dynamic deformable elastic template model for the segmentation of the heart in MRI sequences [Online]. Available: http://hdl.handle.net/10380/3072
13. C. Constantinides, Y. Chenoune, N. Kachenoura, E. Roullot, E. Mousseaux, A. Herment, and F. Frouin, Semi-automated cardiac segmentation on cine magnetic resonance images using GVF-snake deformable models [Online]. Available: http://hdl.handle.net/10380/3108
14. A. Delong and Y. Boykov, "Globally optimal segmentation of multiregion objects," in Int. Conf. Comput. Vis., Kyoto, Japan, 2009.
15. A. V. Goldberg, S. Hed, H. Kaplan, R. E. Tarjan, and R. F.Werneck, "Maximum flows by incremental breadth-first search," in Eur. Symp. Algor., 2011, pp. 457-468.
16. L. Grady, "Random walks for image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 11, pp. 1768-1783, Nov. 2006. (Pubitemid 46405425)
17. L. Grady and M. P. Jolly, "Weights and topology: A study of the effects of graph construction on 3d image segmentation," in Conf.Med. Image Comput. Computer-Assist. Intervent., 2008, pp. 153-161.
18. P. L. Hammer, P. Hansen, and B. Simeone, "Roof duality, complementation and persistency in quadratic 0-1 optimization," Math. Programm., vol. 28, no. 2, pp. 121-155, 1984. (Pubitemid 14569633)
19. E. Heiberg et al., "Design and validation of segment-freely available software for cardiovascular image analysis," BMCMed. Imag., vol. 10, no. 1, p. 1, 2010.
20. S. Hu, E. A. Hoffman, and J. M. Reinhardt, "Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images," IEEE Trans. Med. Imag., vol. 20, no. 6, pp. 490-498, Jun. 2001. (Pubitemid 32657853)
21. S. Huang, J. Liu, L. Lee, S.Venkatesh, L. Teo, C. Au, and W.Nowinski, Segmentation of the left ventricle from cine MR images using a comprehensive approach [Online]. Available: http://hdl.handle.net/10380/3121
22. H. Ishikawa, "Exact optimization for markov random fields with convex priors," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 10, pp. 1132-1139, Oct. 2003.
23. M. Jolly, Fully automatic left ventricle segmentation in cardiac cine MR images using registration and minimum surfaces [Online]. Available: http://hdl.handle.net/10380/3114
24. P. Kohli and P. Torr, "Dynamic graph cuts for efficient inference in Markov random fields," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 12, pp. 2079-2088, Dec. 2007. (Pubitemid 350124058)
25. V. Kolmogorov, "Convergent tree-reweighted message passing for energy minimization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 10, pp. 1568-1583, Oct. 2006. (Pubitemid 46405078)
26. N. Komodakis and G. Tziritas, "Approximate labeling via graph cuts based on linear programming," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 8, pp. 1436-1453, Aug. 2007. (Pubitemid 47040441)
27. X. Lin, B. Cowan, and A. Young, "Model-based graph cut method for segmentation of the left ventricle," Proc. IEEE Eng. Med. Bio. Soc., pp. 3059-3062, Sep. 2006.
28. M. Lorenzo-Valdés et al., "Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm," Med. Image Anal., vol. 8, no. 3, pp. 255-265, 2004. (Pubitemid 39185909)
29. Y. Lu, P. Radau, K. Connelly, A. Dick, and G. Wright, Automatic image-driven segmentation of left ventricle in cardiac cine MRI [Online]. Available: http://hdl.handle.net/10380/3109
30. L. Marak, J. Cousty, L. Najman, and H. Talbot, 4D morphological segmentation and theMICCAI LV-segmentation grand challenge [Online]. Available: http://hdl.handle.net/10380/3085
31. C. McIntosh and G. Hamarneh, "Medial-based deformable models in non-convex shape-spaces for medical image segmentation using genetic algorithms," IEEE Trans. Med. Imag., vol. 31, no. 1, pp. 33-50, Jan. 2012.
32. S. C. Mitchell, B. P. F. Lelieveldt, R. J. van der Geest, H. G. Bosch, J. H. C. Reiber, and M. Sonka, "Multistage hybrid active appearance model matching: Segmentation of left and right ventricles in cardiac MR images," IEEE Trans. Med. Imag., vol. 20, no. 5, pp. 415-423, May 2002. (Pubitemid 32576604)
33. Y. Nesterov, Introductory Lectures on Convex Optimization. Norwell, MA: Kluwer, 2004.
34. S. O'Brien, O. Ghita, and P. Whelan, Segmenting the left ventricle in 3D using a coupled ASM and a learned non-rigid spatial model [Online]. Available: http://hdl.handle.net/10380/3110
35. N. Paragios, "A variational approach for the segmentation of the left ventricle in cardiac image analysis," Int. J. Comput. Vis., vol. 50, no. 3, pp. 345-362, 2002. (Pubitemid 35381598)
36. C. Rother, V. Kolmogorov, V. Lempitsky, and M. Szummer, "Optimizing binary MRFs via extended roof duality," Conf. Comput. Vis. Pattern Recognit., pp. 1-8, 2007.
37. L. X. S. Boyd and A. Mutapcic, Subgradient methods 2003 [Online]. Available: http://www.stanford.edu/class/ee392o/subgrad-method.pdf
38. P. Strandmark and F. Kahl, "Parallel and distributed graph cuts by dual decomposition," in Conf. Comput. Vis. Pattern Recognit., 2010, pp. 2085-2092.
39. S. Ukil and J. M. Reinhardt, "Anatomy-guided lung lobe segmentation in X-ray CT images," IEEE Trans. Med. Imag., vol. 28, no. 2, pp. 202-214, Feb. 2009.
40. J. Ulén, P. Strandmark, and F. Kahl, "Optimization for multi-region segmentation of cardiac MRI," in Proc. MICCAI Workshop Stat. Atlases Computat. Models Heart: Imag. Modell. Chall., 2011, pp. 129-138.
41. J. Wijnhout, D. Hendriksen, H. van Assen, and R. van der Geest, LV challenge LKEB contribution: Fully automatedmyocardial contour detection. [Online]. Available: http://hdl.handle.net/10380/3115