A versatile wavelet domain noise filtration technique for medical imaging

IEEE Transactions on Medical Imaging

Volumn 22, Issue 3, 2003, Pages 323-331

  Pižurica, Aleksandra ^a   Philips, Wilfried ^a   Lemahieu, Ignace ^a   Acheroy, Marc ^b  

^a GHENT UNIVERSITY   (Belgium)

^b ROYAL MILITARY ACADEMY   (Belgium)

Author keywords

Generalized likelihood ratio; Joint detection and estimation; Noise reduction; Wavelets

Indexed keywords

ALGORITHMS; IMAGE ENHANCEMENT; IMAGE QUALITY; MAGNETIC RESONANCE IMAGING; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; ULTRASONIC IMAGING; WAVELET TRANSFORMS;

GENERALIZED LIKELIHOOD RATIO; NOISE SUPPRESSION; WAVELET DOMAIN INDICATOR; WAVELET DOMAIN NOISE FILTRATION TECHNIQUE;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BRAIN; COMPARATIVE STUDY; COMPUTER INTERFACE; COMPUTER SIMULATION; ECHOGRAPHY; EVALUATION; HEART; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; SCINTISCANNING; SIGNAL PROCESSING; STATISTICAL MODEL; STATISTICS; VALIDATION STUDY;

ALGORITHMS; BRAIN; COMPUTER SIMULATION; HEART; HUMANS; IMAGE ENHANCEMENT; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; SIGNAL PROCESSING, COMPUTER-ASSISTED; STOCHASTIC PROCESSES; ULTRASONOGRAPHY; USER-COMPUTER INTERFACE;

EID: 0037983986     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2003.809588     Document Type: Article

References (40)

1. T. Aach and D. Kunz, "Anisotropic spectral amplitude estimation for noise reduction and image enhancement," in Proc. IEEE Int. Conf. Image Processing, Lausanne, Switzerland, 1996, pp. 335-338.
2. F. Abramovich, T. Sapatinas, and B. W. Silverman, "Wavelet thresholding via a Bayesian approach," J. Roy. Statist. Soc. B, vol. 60, pp. 725-749, 1998.
3. A. Achim, A. Bezerianos, and P. Tsakalides, "Novel Bayesian multiscale method for speckle removal in medical ultrasound images," IEEE Trans. Med. Imag., vol. 20, pp. 772-783, Aug. 2001.
4. S. G. Chang, B. Yu, and M. Vetterli, "Spatially adaptive wavelet thresholding with context modeling for image denoising," IEEE Trans. Image Processing, vol. 9, pp. 1522-1531, Sept. 2000.
5. H. A. Chipman, E. D. Kolaczyk, and R. E. McCulloch, "Adaptive Bayesian wavelet shrinkage," J. Amer. Statist. Assoc., vol. 92, pp. 1413-1421, 1997.
6. M. S. Crouse, R. D. Nowak, and R. G. Baranuik, "Wavelet-based statistical signal processing using hidden Markov models," IEEE Trans. Signal Processing, vol. 46, pp. 886-902, Apr. 1998.
7. D. L. Donoho, "De-noising by soft-thresholding," IEEE. Trans. Inform. Theory, vol. 41, pp. 613-627, May 1995.
8. W. A. Edelstein, G. Glover, C. Hardy, and R. Redington, "The intrinistic signal-to-noise ratio in NMR imaging," Magn. Reson. Med., vol. 3, pp. 604-618, 1986.
9. Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean-square error short-time spectral amplitude estimation," IEEE Trans. Acoust. Speech Signal Processing, vol. ASSP-32, pp. 1109-1121, Dec. 1984.
10. G. Fan and X.-G. Xia, "Image denoising using local contextual hidden markov model in the wavelet domain," IEEE Signal Processing Lett., vol. 8, pp. 125-128, May 2001.
11. S. Foucher, G. B. Benie, and J. M. Boucher, "Unsupervised multiscale speckle filtering," in Proc. IEEE Int. Conf. Image Processing, Lausanne, Switzerland, 1996, pp. 391-394.
12. ____, "Multiscale MAP filtering of SAR images," IEEE Trans. Image Processing, vol. 10, pp. 49-60, Jan. 2001.
13. J. W. Goodman, "Some fundamental properties of speckle," J. Opt. Soc. Amer., vol. 66, pp. 1145-1150, 1976.
14. H. Gudbjartsson and S. Patz, "The Rician distribution of noisy MRI data," Magn. Reson. Med., vol. 34, pp. 910-914, 1995.
15. T.-C. Hsung, D. P.-K. Lun, and W.-C. Siu, "Denoising by singularity detection," IEEE Trans. Signal Processing, vol. 47, pp. 3139-3144, Nov. 1999.
16. A. K. Jain, Fundamental of Digital Image Processing, Upper Saddle River, NJ: Prentice-Hall, 1989.
17. M. Jansen and A. Bultheel, "Geometrical priors for noisefree wavelet coefficient configurations in image de-noising," in Bayesian Inference in Wavelet Based Models, P. Müller and B. Vidakovic, Eds. New York: Springer-Verlag, 1999, pp. 223-242.
18. G. Kossof, W. J. Garret, D. A. Carpenter, J. Jellins, and M. J. Dadd, "Principles and classification of soft tissues by gray scale echography," Ultrasound Med. Biol., vol. 2, pp. 89-105, 1976.
19. H. Krim and I. C. Schick, "Minimax description length for signal denoising and optimized representation," IEEE Trans. Inform. Theory, vol. 45, pp. 898-908, Apr. 1999.
20. D. Leporini, J.-C. Pasquet, and H. Krim, "Best basis representation with prior statistical models," in Lecture Notes in Statistics, P. Müller and B. Vidakovic, Eds. New York: Springer-Verlag, 1999, pp. 155-172.
21. X. Li and M. Orchard, "Spatially adaptive denoising under overcomplete expansion," presented at the IEEE Int. Conf. Image Processing, Vancouver, BC, Canada, Sept. 2000.
22. A. Macovski, "Noise in MRI," Magn. Reson. Med., vol. 36, pp. 494-497, 1996.
23. M. Malfait and D. Roose, "Wavelet-based image denoising using a Markov random field a priori model," IEEE Trans. Image Processing, vol. 6, pp. 549-565, Apr. 1997.
24. S. Mallat, "A theory for multiresolution signal decomposition: The wavelet representation," IEEE Trans. Pattern Anal. Machine Intell., vol. 11, pp. 674-693, July 1989.
25. ____, A Wavelet Tour of Signal Processing. New York: Academic, 1998.
26. R. J. McAulay and M. L. Malpass, "Speech enhancement using a soft-decision noise suppression filter," IEEE Trans. Acoust. Speech Signal Processing, vol. ASSP-28, pp. 137-144, Apr. 1980.
27. E. R. McVeigh, R. M. Henkelman, and M. J. Bronskill, "Noise and filtration in magnetic resonance imaging," Med. Phys., vol. 3, pp. 604-618, 1985.
28. D. Middleton and R. Esposito, "Simultaneous optimum detection and estimation of signals in noise," IEEE Trans. Inform. Theory, vol. IT-14, pp. 434-443, May 1968.
29. M. K. Mihçak, I. Kozintsev, K. Ramchandran, and P. Moulin, "Low-complexity image denoising based on statistical modeling of wavelet coefficients," IEEE Signal Processing Lett., vol. 6, pp. 300-303, Dec. 1999.
30. R. D. Nowak, "Wavelet-based rician noise removal for magnetic resonance imaging," IEEE Trans. Image Processing, vol. 8, pp. 1408-1419, Oct. 1999.
31. A. Pižurica, W. Philips, I. Lemahieu, and M. Acheroy, "A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising," IEEE Trans. Image Processing, vol. 11, pp. 545-557, May 2002.
32. A. Pižurica, "Image denoising using wavelets and spatial context modeling," Ph.D. dissertation, Ghent Univ., Ghent, Belgium, 2002.
33. A. Pižurica, W. Philips, I. Lemahieu, and M. Acheroy, "Despeckling SAR images using wavelets and a new class of adaptive shrinkage functions," in IEEE Int. Conf. Image Processing, Thessaloniki, Greece, Oct. 2001.
34. F. Sattar, L. Floreby, G. Salomonsson, and B. Lövström, "Image enhancement based on a nonlinear multiscale method," IEEE Trans. Image Processing, vol. 6, pp. 888-895, June 1997.
35. F. G. Sommer, L. F. Joynt, B. A. Carroll, and A. Macowski, "Ultrasonic characterization of abdominal tissues via digital analysis of backscattered waveforms," Radiol., vol. 141, pp. 811-817, Dec. 1981.
36. M. Unser and A. Aldroubi, "A review of wavelets in biomedical applications," Proc. IEEE, vol. 84, pp. 626-634, Apr. 1996.
37. B. Vidakovic, "Wavelet-based nonparametric Bayes methods," In Practical Nonparametric and Semiparametric Bayesian Statistics, D. D. Dey, P. Müller, and D. Sinha, Eds. New York: Springer-Verlag, 1998. Lecture Notes in Statistics 133, pp. 133-155.
38. Y. Xu, J. B. Weaver, D. M. Healy, and J. Lu, "Wavelet transform domain filters: A spatially selective noise filtration technique," IEEE Trans. Image Processing, vol. 3, pp. 747-758, Nov. 1994.
39. R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, "Statistics of speckle in ultrasound B-scans," IEEE Trans. Sonics Ultrason., vol. SU-30, pp. 156-163, May 1983.
40. J. Weaver, Y. Xu, D. Healy, and J. Driscoll, "Filtering MR images in the wavelet transform domain," Magn. Reson. Med., vol. 21, pp. 288-295, 1991.