Comparison of bootstrap resampling methods for 3-D PET imaging

IEEE Transactions on Medical Imaging

Volumn 29, Issue 7, 2010, Pages 1442-1454

  Lartizien, C ^a   Aubin, J B ^b   Buvat, I ^c  

^a UNIVERSITÉ DE LYON   (France)

^b UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

^c Centre National de la Recherche Scientifique   (France)

Author keywords

Bootstrap; noise properties; positron emission tomography (PET)

Indexed keywords

BOOTSTRAP; BOOTSTRAP APPROACH; BOOTSTRAP METHOD; BOOTSTRAP RESAMPLING; CLINICAL DATA; DATA SAMPLE; DATA SETS; HIGH NOISE LEVELS; LISTMODE; LOWER NOISE; NOISE PROPERTIES; NON-PARAMETRIC; NONPARAMETRIC APPROACHES; ORIGINAL SAMPLE; PARAMETRIC APPROACH; PET IMAGING; RESAMPLING; SECOND GROUP; SIMULATED DATA; SINOGRAMS; STATISTICAL MOMENTS; STATISTICAL PARAMETERS; STATISTICAL PROPERTIES;

ELECTRONS; POISSON DISTRIBUTION; POSITRONS; PROBABILITY DENSITY FUNCTION; SAMPLING; THREE DIMENSIONAL;

POSITRON EMISSION TOMOGRAPHY;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; POSITRON EMISSION TOMOGRAPHY; REPRODUCIBILITY; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; POSITRON-EMISSION TOMOGRAPHY; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 77954240137     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2010.2048119     Document Type: Article

References (24)

1. H. H. Barrett, "Objective assessment of image quality: Effects of quantum noise and object variability," J. Opt. Soc. Amer., vol.7, pp. 1266-1278, 1990.
2. N. M. Alpert, D. A. Chesler, J. A. Correia, R. H. Ackerman, J. Y. Chang, S. Finklestein, S. M. Davis, G. L. Brownell, and J. Taveras, "Estimation of the local statistical noise in emission computed tomography," IEEE Trans. Med. Imag., vol.1, no.2, pp. 142-146, Oct. 1982.
3. L. D. Nickerson, S. Narayana, J. L. Lancaster, P. T. Fox, and J.-H. Gao, "Estimation of the local statistical noise in positron emission tomography revisited: Practical implementation," Neuroimage, vol.19, no.2, pp. 442-456, 2003.
4. H. H. Barrett, D. W. Wilson, and B. M. W. Tsui, "Noise properties of the EM algorithm: I. Theory," Phys. Med. Biol., vol.39, pp. 833-846, 1994.
5. E. J. Soares, C. L. Byrne, and S. J. Glick, "Noise characterization of block-iterative reconstruction algorithms: 1. Theory," IEEE Trans. Med. Imag., vol.19, no.4, pp. 261-270, Apr. 2000.
6. J. Qi and R. M. Leahy, "Resolution and noise properties of MAP reconstruction for fully 3-D PET," IEEE Trans. Med. Imag., vol.19, no.5, pp. 493-506, May 2000.
7. B. Efron and R. J. Tibshirani, An Introduction to the Bootstrap, CRC ed. New York: Chapman Hall, 1993.
8. D. R. Haynor and S. D. Woods, "Resampling estimates of precision in emission tomography," IEEE Trans. Med. Imag., vol.8, no.4, pp. 337-343, Dec. 1989.
9. I. Buvat, "A non-parametric bootstrap approach for analysing the statistical properties of SPECT and PET images," Phys. Med. Biol., vol.47, pp. 1761-1775, 2002.
10. M. Dahlbom, "Estimation of image noise in PET using the bootstrap method," IEEE Trans. Nucl. Sci., vol.49, no.5, pp. 2062-2066, Oct. 2002.
11. J.-S. Kim, R. S. Miyaoka, R. L. Harrisson, P. E. Kinahan, and T. K. Lewellen, "Detectability comparisons of image reconstruction algorithms using the channelized hotelling observer with bootstrap resam-pled data," in Proc. IEEE Nucl. Sci. Symp. Med. Imag. Conf., Norfolk, VA, 2002, pp. 1444-1448.
12. Y. D'Asseler, C. J. Groiselle, H. C. Gifford, S. Vandenberghe, R. Van de Walle, I. L. Lemahieu, and S. J. Glick, "Evaluating numerical observer performance for list mode PET using the bootstrap method," in Proc. IEEE Nucl. Sci. Symp. Med. Imag. Conf., Portland, OR, 2003, pp. 3070-3073.
13. S. Jan, G. Santin, D. Strul, S. Staelens, K. Assié, D. Autret, S. Avner, R. Barbier, M. Bardiès, P. M. Bloomfield, D. Brasse, V. Breton, P. Bruyndonckx, I. Buvat, A. F. Chatziioannou, Y. Choi, Y. H. Chung, C. Comtat, D. Donnarieix, L. Ferrer, S. J. Glick, C. J. Groiselle, D. Guez, P. F. Honore, S. Kerhoas-Cavata, A. S. Kirov, V. Kohli, M. Koole, M. Krieguer, D. J. Van der Laan, F. Lamare, G. Largeron, C. Lartizien, D. Lazaro, M. C. Maas, L. Maigne, F. Mayet, F. Melot, C. Merheb, E. Pennacchio, J. Perez, U. Pietrzyk, F. R. Rannou, M. Rey, D. R. Schaart, C. R. Schmidtlein, L. Simon, T. Y. Song, J. M. JVieira, D. Visvikis, R. Van de Walle, E. Wieërs, and C. Morel, "GATE: A simulation toolkit for PET and SPECT," Phys. Med. Biol., pp. 4543-4561, 2004.
14. C. Knoess, S. Siegel, A. Smith, D. Newport, N. Richerzhagen, A. Winkeler, A. Jacobs, R. N. Goble, R. Graf, K. Wienhard, and W.-D. Heiss, "Performance evaluation of the microPET R4 PET scanner for rodents," Eur. J. Nucl. Med. Mol. Imag., vol.30, pp. 737-747, 2003.
15. List mode format (LMF) [Online]. Available: http://opengatecollabo- ration.healthgrid.org/GATEusers/documentation
16. K. Thielemans, STIR 1.4, Software Library and Documentation 2004 [Online]. Available: http://stir.sourceforge.net/
17. I. W. Hsu, C.-H. Hsu, I.-T. Hsiao, and K. M. Lin, "On the convergence of iterative ordered-subset algorithms in small animal PET," in Proc. IEEE Nucl. Sci. Symp. Med. Imag. Conf., Dresden, Germany, 2008, pp. 5125-5128.
18. D. W. Wilson, B. Tsui, and H. H. Barrett, "Noise properties of the EM algorithm: II. Monte Carlo simulations," Phys. Med. Biol., vol.39, no.5, pp. 847-871, 1994.
19. E. J. Soares, S. J. Glick, and J. W. Hoppin, "Noise characterization of block-iterative reconstruction algorithms: II. Monte Carlo simulations," IEEE Trans. Med. Imag., vol.24, no.1, pp. 112-121, Jan. 2005.
20. P. Sprent and N. C. Smeeton, Applied Nonparametric Statistical Methods. London, U.K.: Chapman Hall, 2001, vol.1.
21. P. Tylski, M. Dusart, H. Necib, B. Vanderlinden, and I. Buvat, "A method to assign statistical significance to SUV changes in patient follow-up with FDG-PET," J. Nucl. Med., p. 383P, 2008.
22. H. H. Barrett, J. Yao, J. P. Rolland, and K. J. Myers, "Model observers for assessment of image quality," Proc. Nat. Acad. Sci., vol.90, no.21, pp. 9758-9765, 1993.
23. C. Lartizien, S. Tomei, and S. Marache-Francisco, "Improving performance of automated detection systems for 3-D PET oncology imaging by use of resampled training images," Int. J. Comput. Assist. Radiol. Surg., vol.4, pp. S186-193, 2009.
24. R.J. Larsen andM. L.Marx, An Introduction to Mathematical Statistics and Its Applications. New York: Prentice Hall, 2005.