Multiphase B-spline level set and incremental shape priors with applications to segmentation and tracking of left ventricle in cardiac MR images

Machine Vision and Applications

Volumn 25, Issue 8, 2014, Pages 1967-1987

  Pham, Van Truong ^a   Tran, Thi Thao ^a   Shyu, Kuo Kai ^a   Lin, Lian Yu ^b   Wang, Yung Hung ^a   Lo, Men Tzung ^a  

^a NATIONAL CENTRAL UNIVERSITY   (Taiwan)

^b NATIONAL TAIWAN UNIVERSITY HOSPITAL   (Taiwan)

Author keywords

Image segmentation; Incremental PCA; Left ventricle tracking; Level set method; Shape prior

Indexed keywords

GRADIENT METHODS; HEART; INTERPOLATION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; NUMERICAL METHODS; OBJECT TRACKING; PARTIAL DIFFERENTIAL EQUATIONS; SPLINES;

CARDIAC MAGNETIC RESONANCE IMAGES; COUPLED PARTIAL DIFFERENTIAL EQUATIONS; INCREMENTAL PCA; INCREMENTAL PRINCIPAL COMPONENT ANALYSIS; LEFT VENTRICLES; LEVEL SET METHOD; SEGMENTATION AND TRACKING; SHAPE PRIORS;

IMAGE SEGMENTATION;

EID: 84919876301     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-014-0626-1     Document Type: Article

References (56)

1. Lynch, M., Ghita, O., Whelan, P.F.: Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model. IEEE Trans. Med. Imaging 27(2), 195–203 (2008)
2. Zhu, Y., Papademetris, X., Sinusas, J.A., Duncan, S.J.: Segmentation of the left ventricle from cardiac MR images using a subject-specific dynamical model. IEEE Trans. Med. Imaging 29(3), 669–687 (2010)
3. Santarelli, M.F., Positano, V., Michelassi, C., Lombardi, M., Landini, L., Barlaud, M.: Automated cardiac MR image segmentation: theory and measurement evaluation. Med. Eng. Phys. 25(2), 149–159 (2003)
4. Kaus, R.M., Von Berg, J., Weese, J., Niessen, W., Pekar, V.: Automated segmentation of the left ventricle in cardiac MRI. Med. Image Anal. 8(3), 245–254 (2004)
5. Duy, N., Karen, M., Jean-Paul, V.: Comparative evaluation of active contour model extensions for automated cardiac MR image segmentation by regional error assessment. Magn. Reson. Mater. Phys. 20(2), 69–82 (2007)
6. Kurkure, U., Pednekar, A., Muthupillai, R., Flamm, D.S., Kakadiaris, A.L.: Localization and segmentation of left ventricle in cardiac Cine-MR images. IEEE Trans. Biomed. Eng. 56(5), 1360–1370 (2009)
7. Tsai, I.C., Huang, Y.L., Liu, P.T., Chen, M.C.: Left ventricular myocardium segmentation on delayed phase of multi-detector row computed tomography. Int. J. Comput. Assist. Radiol. Surg. 7(5), 737–751 (2012)
8. Rezaee, M., van der Zwet, P., Lelieveldt, B., van der Geest, R., Reiber, J.: A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering. IEEE Trans. Image Process. 9(7), 1238–1248 (2000)
9. Boykov, Y., Lee, V.S., Rusinek, H., Bansal, R.: Segmentation of dynamic N-d data sets via graph cuts using markov models. In: Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (mICCAI), pp. 1058–1066 (2001)
10. Mahapatra, D., Sun, Y.: Orientation histograms as shape priors for left ventricle segmentation using graph cuts. In: Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 420–427 (2011)
11. Hautvast, G., Lobregt, S., Breeuwer, M., Gerritsen, F.: Automatic contour propagation in cine cardiac magnetic resonance images. IEEE Trans. Med. Imaging 25(11), 1472–1482 (2006)
12. Marsousi, M., Eftekhari, A., Kocharian, A., Alirezaie, J.: Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline snake algorithm. Int. J. Comput. Assist. Radiol. Surg. 5(5), 501–513 (2010)
13. Grosgeorge, D., Petitjean, C., Caudron, J., Fares, J., Nicolas Dacher, J.: Automatic cardiac ventricle segmentation in MR images: a validation study. Int. J. Comput. Assist. Radiol. Surg. 6(5), 573–581 (2011)
14. Andreopoulos, A., Tsotsos, J.K.: Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI. Med. Image Anal. 12(3), 335–357 (2008)
15. Cremers, D., Rousson, M., Deriche, R.: A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape. Int. J. Comput. Vis. 72(5), 195–215 (2007)
16. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis. 1(4), 321–331 (1988)
17. Sethian, J.A.: Level set methods and fast marching methods. Cambridge University Press, Cambridge (1999)
18. Caselles, V., Catte, F., Coll, T., Dibos, F.: A geometric model for active contours in image processing. Numer. Math. 66(1), 1–31 (1993)
19. Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. Int. J. Comput. Vis. 22(1), 61–79 (1997)
20. Chan, T., Vese, L.: Active contours without edges. IEEE Trans. Image Process. 10(2), 266–277 (2001)
21. Ronfard, R.: Region-based strategies for active contour models. Int. J. Comput. Vis. 13(2), 229–251 (1994)
22. Shyu, K.K., Pham, V.T., Tran, T.T., Lee, P.L.: Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation. Mach. Vis. Appl. 23(6), 1159–1175 (2012)
23. Vese, L., Chan, T.: A multiphase level set framework for image segmentation using the Mumford and Shah model. Int. J. Comput. Vis. 50(3), 271–293 (2002)
24. Bresson, X., Vandergheynst, P., Thiran, J.P.: A variational model for object segmentation using boundary information and shape prior driven by the Mumford–Shah functional. Int. J. Comput. Vis. 28(2), 145–162 (2006)
25. Chen, Y., Tagare, H.D., Thiruvenkadam, S., Huang, F., Wilson, D., Gopinath, K.S., Briggs, R.W., Geiser, E.A.: Using prior shapes in geometric active contours in a variational framework. Int. J. Comput. Vis. 50(3), 315–328 (2002)
26. Paragios, N.: A variational approach for the segmentation of the left ventricle in cardiac image analysis. Int. J. Comput. Vis. 50(3), 345–362 (2002)
27. Zhang, S., Zhan, Y., Dewan, M., Huang, J., Metaxas, D.N., Zhou, X.S.: Sparse shape composition: a new framework for shape prior modeling. In: Proceedings of Computer Vision and Pattern Recognition (CVPR), pp. 1025–1032 (2011)
28. Petitjean, C., Dacher, J.N.: A review of segmentation methods in short axis cardiac MR images. Med. Image Anal. 15(2), 169–184 (2011)
29. Qin., X., Li, X., Liu, Y., Lu, H., Yan, P.: Adaptive shape prior constrained level sets for bladder MR image segmentation. IEEE J. Biomed. Health Inf. (2013). doi:10.1109/JBHI.2013.2288935
30. Tsai, A., Yezzi, A., Wells, W., Temany, C., Tucker, D., Fan, A., Grimson, W.E., Willsky, A.: A shape-based approach to the segmentation of medical imagery using level sets. IEEE Trans. Med. Imaging 22(2), 137–154 (2003)
31. Leventon, M., Grimson, E., Faugeras, O.: Statistical shape influence in geodesic active contours. In: Proceedings of Computer Vision and Pattern Recognition (CVPR), Hilton Head Island, SC, USA, pp. 316–323 (2000)
32. Tsai, A., Wells, W., Tempany, C., Grimson, E., Willsky, A.: Mutual information in coupled multi-shape model for medical image segmentation. Med. Image Anal. 8(4), 429–445 (2004)
33. Rousson, M., Paragios, N., Deriche, R.: implicit active shape models for 3D segmentation in MRi imaging. In: Proceedings of International Conference on Medical image Computing and Computer Assisted intervention (MiCCAi) (2004)
34. Dambreville, S., Rathi, Y., Tannenbaum, A.: A framework for image segmentation using shape models and Kernel space shape priors. IEEE Trans. Pattern Anal. Mach. Intell. 30(8), 1385–1399 (2008)
35. Chan, T., Zhu, W.: Level set based shape prior segmentation. In: Proceedings of Computer Vision and Pattern Recognition (CVPR), San Diego, CA, USA, pp. 1164–1170 (2005)
36. Riklin-Raviv, T., Kiryati, N., Sochen, N.: Prior-based segmentation and shape registration in the presence of projective distortion. Int. J. Comput. Vis. 72(3), 309–328 (2007)
37. Cremers, D., Osher, S.J., Schnorr, C.: Kernel density estimation and intrinsic alignment for shape priors in level set segmentation. Int. J. Comput. Vis. 69(3), 335–351 (2006)
38. Leu, J.G.: Shape normalization through compacting. Pattern Recognit. Lett. 10(4), 243–250 (1989)
39. Pei, S., Lin, C.: Image normalization for pattern recognition. Image Vis. Comput. 13(10), 711–723 (1995)
40. Ross, D., Lim, J., Lin, R.-S., Yang, M.-H.: Incremental learning for robust visual tracking. Int. J. Comput. Vis. 77(1), 125–141 (2008)
41. Mumford, D., Shah, J.: Optimal approximations by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math. 42(5), 577–685 (1989)
42. Aubert, G., Barlaud, M., Faugeras, O., Jehan-Besson, S.: Image segmentation using active contours: calculus of variations or shape gradients? SIAM Appl. Math. 63(6), 2128–2154 (2003)
43. Bernard, O., Friboulet, D., Thevenaz, P., Unser, M.: Variational B-spline level-set: A linear filtering approach for fast deformable model evolution. IEEE Trans. Image Process. 18(6), 1179–1191 (2009)
44. Unser, M.: Splines: a perfect fit for signal and image processing. IEEE Signal Process. Mag. 16(6), 22–38 (1999)
45. Kybic, J., Unser, M.: Fast parametric elastic image registration. IEEE Trans. Image Process. 12(11), 1427–1442 (2003)
46. Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active shape models—their training and application. Comput. Vis. Image Underst. 61(1), 38–59 (1995)
47. Levy, A., Lindenbaum, M.: Sequential Karhunen–Loeve basis extraction and its application to images. IEEE Trans. Image Process. 9(8), 1371–1374 (2000)
48. Vu, N., Manjunath, B.S.: Shape prior segmentation of multiple objects with graph cuts. In: Proceedings of Computer Vision and Pattern Recognition (CVPR), Anchorage, AK (2008)
49. Tran, T.T., Pham, V.T., Shyu, K.K.: Moment-based alignment for shape prior with variational B-spline level set. Mach. Vis. Appl. 24(5), 1075–1091 (2013)
50. Suk, T., Flusser, J.: Affine normalization of symmetric objects. In: Proceedings of the 7th International Conference on Advanced Concepts for Intelligent Vision Systems, pp. 100–107 (2005)
51. Dambreville, S., Rathi, Y., Tannenbaum, A.: A shape-based approach to robust image segmentation. In: Campilho, A.C., Mohamed S.K. (eds.) Proceedings of the Third International Conference on Image Analysis and Recognition, pp. 173–183. Springer, Berlin (2006)
52. Tohka, J.: Surface extraction from volumetric images using deformable meshes: a comparative study. In: Proceedings of the Seventh European Conference in Computer Vision (ECCV), Copenhagen, Denmark, pp. 350–364 (2002)
53. Woo, J.-H., Slomka, P., Kuo, J., Hong, B.-W.: Multiphase segmentation using an implicit dual shape prior: application to detection of left ventricle in cardiac MRI. Comput. Vis. Image Underst. 117(9), 1084–1094 (2013)
54. Song, Q., Wu, X., Liu, Y., Garvin, M., Sonka, M.: Simultaneous searching of globally optimal interacting surfaces with shape priors. In: Proceedings of Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, pp. 2879–2886 (2010)
55. Bland, J., Altman, D.: Statistical methods for assessing agreement between two methods of clinical measurements. Lancet 1, 307–310 (1986)
56. El Berbari, R., Bloch, I., Redheuil, A., Angelini, E.D., Mousseaux, E., Frouin, F., Herment, A.: Automated segmentation of the left ventricle including papillary muscles in cardiac magnetic resonance images. In: Proceedings of Functional Imaging Modelling of the Heart (2007)