Graph-based mumford-shah segmentation of dynamic PET with application to input function estimation

IEEE Transactions on Nuclear Science

Volumn 52, Issue 1 I, 2005, Pages 79-89

  Parker, Brian J ^a   Feng, Dagan ^a,b  

^a UNIVERSITY OF SYDNEY   (Australia)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Brain modeling; Covariance analysis; Graph theory; Image segmentation; Mumford shah; Pattern recognition; Positron emission tomography

Indexed keywords

BRAIN MODELING; COVARIANCE ANALYSIS; MUMFORD-SHAH; TIME ACTIVITY CURVES (TAC);

ALGORITHMS; BRAIN; COMPUTER SIMULATION; GRAPH THEORY; IMAGE SEGMENTATION; MATHEMATICAL MODELS; OPTIMIZATION; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

POSITRON EMISSION TOMOGRAPHY;

EID: 17644373788     PISSN: 00189499     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNS.2004.843133     Document Type: Article

References (29)

1. 18F-Fluoro-2- Deoxyglucose, the Patlak method, and an image-derived input function," J. Cereb. Blood Flow Metab., vol. 18, pp. 716-723, 1998.
2. J. Litton, "Input function in PET brain studies using MR-defined arteries," J. Comput. Assist. Tomog., vol. 21, no. 6, pp. 907-909, 1997.
3. R. Trebossen et al., "Quantifying cerebral PET with FDG using dynamic internal carotid arteries imaging," in Proc. IEEE Conf. Rec. Nuclear Science Symp. Medical Imaging, vol. 3, 1998, pp. 1733-1736.
4. R. Gonzalez and R. Woods, Digital Image Processing, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 2002.
5. J. Ashburner, J. Haslan, C. Taylor, V. J. Cunningham, and T. Jones, "A cluster analysis approach for the characterization of dynamic PET data," in Quantification of Brain Function Using PET, R. Myers, V. Cunningham, D. Bailey, and T. Jones, Eds. San Diego, CA: Academic, 1996, pp. 301-306.
6. K. P. Wong, D. Feng, S. Meikle, and M. Fulham, "Segmentation of dynamic PET images using cluster analysis," IEEE Trans. Nucl. Sci., vol. 49, no. 1, pp. 200-207, Feb. 2002.
7. J. Chen, S. Gunn, M. Nixon, and R. Gunn, "Markov random field models for segmentation of PET images," in IPMI2001, LNCS 2082. Berlin, Germany: Springer-Verlag, 2001, pp. 468-474.
8. Y. Kimura, M. Senda, and N. M. Alpert, "Fast formation of statistically reliable FDG parametric images based on clustering and principal components," Phys. Med. Biol., vol. 47, pp. 455-468, 2002.
9. J. Brankov, N. Galatsanos, Y. Yang, and M. Wernick, "Segmentation of dynamic PET or fMRI images based on a similarity metric," IEEE Trans. Nucl. Sci., vol. 50, no. 5, pp. 1410-1414, Oct. 2003.
10. D. Mumford and J. Shah, "Boundary detection by minimizing functionals," in Image Understanding, S. Ullman and W. Richards, Eds. Norwood, NJ: Ablex, 1988.
11. J. Morel and S. Solimini, Variational Methods in Image Segmentation. Cambridge, MA: Birkhauser, 1995.
12. J. Shah, "A common framework for curve evolution, segmentation and anisotropic diffusion," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1996, pp. 136-142.
13. B. J. Parker and D. Feng, "Large three-dimensional data set segmentation using graph-theoretic energy-minimization approach," in Proc. SPIE Medical Imaging, vol. 5032, San Diego, CA, Feb. 2003, pp. 491-499.
14. F. Pederson, M. Bergstrom, E. Bengtsson, and B. Langstrom, "Principal component analysis of dynamic positron emission tomography images," Eur. J. Nucl. Med., vol. 21, pp. 1285-1292, 1994.
15. M. Samal, M. Karny, H. Benali, W. Backfrieder, A. Todd-Pokropek, and H. Bergmann, "Experimental comparison of data transformation procedures for analysis of principal components," Phys. Med. Biol., vol. 44, pp. 2821-2834, 1999.
16. Z. Chen, B. J. Parker, and D. Feng, "Temporal processing of dynamic positron emission tomography via principal component analysis in the sinogram domain," IEEE Trans. Nucl. Sci., vol. 51, no. 5, pp. 2612-2619, Oct. 2004.
17. G. Koepfler, C. Lopez, and J. M. Morel, "A multiscale algorithm for image segmentation by variational method," SIAM J. Numer, Anal., vol. 31, n. 1, pp. 282-299, 1994.
18. N. J. Redding, D. J. Crisp, D. H. Tang, and G. N. Newsam, "An efficient algorithm for Mumford-Shah segmentation and its application to SAR imagery," in Proc. Conf. Digital Image Computing Techniques and Applications (DICTA '99), 1999, pp. 35-41.
19. E. Hoffman, S. C. Huang, and M. Phelps, "Quantitation in positron emission computed tomography: 1. Effects of object size," J. Comput. Assist. Tomog., vol. 3, no. 3, pp. 299-308, Jun. 1979.
20. J. W. Keyes, "SUV: standard uptake or silly useless value?" J. Nucl. Med., vol. 36, no. 10, pp. 1837-1839, Oct. 1995.
21. B. J. Parker and D. Feng, "Graph-based energy-minimization segmentation and PCA applied to internal carotid extraction in neurological PET," in Proc. IEEE Conf. Rec. Nuclear Science Symposium and Medical Imaging, vol. 4, Portland, OR, Oct. 2003, pp. 2613-2617.
22. S. S. Gambhir, M. Schwaiger, and S. C. Huang et al., "Simple noninvasive quantification method for measuring myocardial glucose utilization in humans employing positron emission tomography and fluorine-18-deoxyglucose, " J. Nucl. Med., vol. 30, pp. 359-366, 1989.
23. T. Ohtake, N. Kosaka, T. Watanabe, and I. Yokoyama et al., "Noninvasive method to obtain input function for measuring tissue glucose utilization of thoracic and abdominal organs," J. Nucl. Med., vol. 32, no. 7, July 1991.
24. I. G. Zubal, C. R. Harrell, E. O. Smith, Z. Rattner, G. Gingi, and P. B. Hoffer, "Computerized three-dimensional segmented human anatomy," Med. Phys., vol. 21, pp. 299-302, 1994.
25. X. Li, D. Feng, and K. Chen, "Optimal image sampling schedule: a new effective way to reduce dynamic image storage space and functional image processing time," IEEE Trans. Med. Imag., vol. 15, no. 5, pp. 710-719, Oct. 1996.
26. M. Phelps, S.-C. Huang, E. J. Huffman, C. Selin, L. Sokoloff, and D. E. Kuhl, "Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-decoxy-D-glucose: validation of method," Ann. Neurol., vol. 6, pp. 371-388, 1979.
27. R. A. Hawkins, M. E. Phelps, and S. C. Huang, "Effects of temporal sampling, glucose metabolic rates, and disruptions of the blood-brain barrier on the FDG model with and without a vascular compartment: studies in human brain tumors with PET," J. Cereb. Blood Flow Metab., vol. 6, pp. 170-183, 1996.
28. D. D. Feng, D. Ho, K. Chen, L.-C. Wu, J.-K. Wang, R.-S. Liu, and S.-H. Yeh, "An evaluation of the algorithms for determining local cerebral metabolic rates of glucose using positron emission tomography dynamic data," IEEE Trans. Med. Imag., vol. 14, no. 4, Dec. 1995.
29. J. Litton and L. Eriksson, "Transcutaneous measurement of the arterial input function in positron emission tomography," IEEE Trans. Nucl, Sci., vol. 37, no. 2, pp. 627-628, Apr. 1990.