Limited view CT reconstruction and segmentation via constrained metric labeling

Computer Vision and Image Understanding

Volumn 112, Issue 1, 2008, Pages 67-80

  Singh, Vikas ^a   Mukherjee, Lopamudra ^b   Dinu, Petru M ^c   Xu, Jinhui ^b   Hoffmann, Kenneth R ^c  

^a UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^b UNIVERSITY OF WISCONSIN WHITEWATER   (United States)

^c UNIVERSITY AT BUFFALO   (United States)

Author keywords

Coronary vessel rotational angiography; Limited view CT reconstruction; Linear programming; MRF with special constraints; Randomized rounding; Segmentation

Indexed keywords

COMPUTERIZED TOMOGRAPHY; DIAGNOSTIC RADIOGRAPHY; ELECTRIC INSTRUMENT TRANSFORMERS; IMAGING TECHNIQUES; LABELING; LINEAR PROGRAMMING; LINEARIZATION; MEDICAL IMAGING; RESTORATION; SET THEORY; THERMOGRAPHY (TEMPERATURE MEASUREMENT); TOMOGRAPHY;

ATTENUATION COEFFICIENTS; CLINICAL APPLICATIONS; CONE-BEAM COMPUTED TOMOGRAPHY; CORONARY VESSEL ROTATIONAL ANGIOGRAPHY; CT RECONSTRUCTIONS; DISCRETE OPTIMIZATION; FINITE SETS; INPUT RECONSTRUCTION; LIMITED VIEW CT RECONSTRUCTION; METRIC LABELING; METRIC LABELING PROBLEM; MRF WITH SPECIAL CONSTRAINTS; PROGRAMMING FRAMEWORKS; RANDOMIZED ROUNDING; SEGMENTATION; TOMOGRAPHIC RECONSTRUCTIONS; UNIFIED MODELING;

REPAIR;

EID: 52949131864     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2008.06.005     Document Type: Article

References (36)

1. Jiang M., and Wang G. Convergence of the simultaneous algebraic reconstruction technique (sart). IEEE Transactions on Image Processing 12 8 (2003)
2. Zhang Y., Chan H.-P., Sahiner B., Wei J., Goodsitt M.M., Hadjiiski L.M., Ge J., and Zhou C. A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis. Medical Physics 33 10 (2006) 3781-3795
3. Rantala M., Vänskä S., Järvenpä S., Kalke M., Lassas M., Moberg J., and Siltanen S. Wavelet-based reconstruction for limited angle X-ray tomography. IEEE Transactions on Medical Imaging 25 2 (2006) 210-217
4. Kolehmainen V., Vanne A., Siltanen S., Järvenpää S., Kaipio J.P., Lassas M., and Kalke M. Parallelized bayesian inversion for three-dimensional dental X-ray imaging. IEEE Transactions on Medical Imaging 25 2 (2006) 218-228
5. V. Singh, P.M. Dinu, L. Mukherjee, J. Xu, K.R. Hoffmann, Limited view CT reconstruction via constrained metric labeling, in: Proceedings of IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis, 2007.
6. Nassi M., Brody W.R., Medoff B.P., and Macovski A. Iterative reconstruction-reprojection: An algorithm for limited data cardiac-computed tomography. IEEE Transactions on Biomedical Engineering 29 (1982) 333-341
7. Kim J.H., Kwak K.Y., Park S.B., and Cho Z.H. Projection space iteration reconstruction-projection. IEEE Transactions on Medical Imaging 4 (1985) 139-143
8. Anderson A.H. Algebraic reconstruction in CT from limited views. IEEE Transactions on Medical Imaging 8 1 (1989) 50-55
9. Velikina J., Leng S., and Chen G.-H. Limited view angle tomographic image reconstruction via total variation minimization. Proceedings of SPIE 6510 1 (2007)
10. J. Fessler, Object-based 3D reconstruction of arterial trees from a few projections. Ph.D. thesis, Stanford University, 1990.
11. A. Rangarajan, Tutorial on the EM algorithm. Available from: http://www.cise.ufl.edu/anand/pdf/mixem.pdf, 1998.
12. Fishburn P., Schwander P., Shepp L., and Vanderbei R.J. The discrete radon transform and its approximate inversion via linear programming. Discrete Applied Mathematics 75 1 (1997) 39-61
13. Gritzmann P., de Vries S., and Wiegelmann M. Approximating binary images from discrete X-rays. SIAM Journal on Optimization 11 2 (2000) 522-546
14. Weber S., Schüle T., Schnörr C., and Hornegger J. A linear programming approach to limited angle 3d reconstruction from dsa projections. Methods of Information in Medicine 43 4 (2004) 320-326
15. Schule T., Schnorr C., Weber S., and Hornegger J. Discrete tomography by convex-concave regularization and d.c. programming. Discrete Applied Mathematics 151 1-3 (2005) 229-243
16. Pruessmann K.P., Weiger M., Scheidegger M., and Boesiger P. SENSE: Sensitivity encoding for fast mri. Magnetic Resonance in Medicine 42 (1999) 952-962
17. Raj A., Singh G., Zabih R., Kressler B., Wang Y., Schuff N., and Weiner M. Bayesian parallel imaging with edge-preserving priors. Magnetic Resonance in Medicine 57 (2007) 8-21
18. Lustig M., L Donoho D., and M Pauly J. Sparse MRI: The application of compressed sensing for rapid mr imaging. Magnetic Resonance in Medicine 58 6 (2007) 1182-1195
19. A. Raj, Improvements in Magnetic Resonance Imaging using Information Redundancy, Ph.D. thesis, Cornell University, May 2005.
20. Kleinberg J., and Tardos E. Approximation algorithms for classification problems with pairwise relationships: metric labeling and markov random fields. Journal of the ACM 49 5 (2002) 616-639
21. Boykov Y., Veksler O., and Zabih R. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence 23 11 (2001) 1222-1239
22. Hochbaum D.S. An efficient algorithm for image segmentation, markov random fields and related problems. Journal of the ACM 48 2 (2001) 686-701
23. Li S.Z. Markov Random Field Modeling in Computer Vision (1995), Springer-Verlag
24. Hoffmann K.R., Nazareth D.P., Miskolczi L., Gopal A., Wang Z., Rudin S., and Bednarek D.R. Vessel size measurements in angiograms: A comparison of techniques. Medical Physics 29 7 (2002) 1622-1633
25. H. Ishikawa, D. Geiger, Segmentation by grouping junctions, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1998, pp. 125-131.
26. Kleinberg J., and Tardos E. Algorithm Design (2005), Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA Chapter 8
27. Goemans M.X., and Williamson D.P. New frac(3, 4)-approximation algorithms for the maximum satisfiability problem. SIAM Journal on Discrete Mathematics 7 4 (1994) 656-666
28. Kolliopoulos S.G., and Young N.E. Approximation algorithms for covering/packing integer programs. Journal of Computer and System Sciences 71 4 (2005) 495-505
29. A. Srivastav and P. Stangier, Integer multicommodity flows with reduced demands, in: Proceedings of European Symposium on Algorithms, 1993, pp. 360-371.
30. Bertsimas D., and Vohra R. Rounding algorithms for covering problems. Mathematical Programming 80 1 (1998) 63-89
31. Mitzenmacher M., and Upfal E. Probability and Computing: Randomized Algorithms and Probabilistic Analysis (2005), Cambridge University Press, New York, NY, USA
32. Angluin D., and Valiant L.G. Fast probabilistic algorithms for hamiltonian circuits and matchings. Journal of Computer and System Sciences 18 2 (1979) 155-193
33. H. Fohlin, L. Kliemann, A. Srivastav, Randomized algorithms for mixed matching and covering in hypergraphs in 3d seed reconstruction in brachytherapy, Technical Report 0611, Institut für Informatik, Christian-Albrechts-Universität zu Kiel, 2006.
34. D. Tschumperle, The C++ Template Image Processing Library (CImg). Available from: http://cimg.sourceforge.net.
35. Kolmogorov V., and Zabih R. What energy functions can be minimized via graph cuts?. IEEE Transactions on Pattern Analysis and Machine Intelligence 26 2 (2004) 147-159
36. D. Freedman, P. Drineas, Energy minimization via graph cuts: settling what is possible, in: IEEE Conference on Computer Vision and Pattern Recognition, 2005, pp. 939-946.