Medical Image Analysis
Volume 14, Issue 2 , Pages 205-218 , April 2010

DWI filtering using joint information for DTI and HARDI

Received 12 November 2008 ,Revised 5 August 2009 ,Accepted 9 November 2009.

References 

  1. Aja-Fernández S, Alberola-López C, Westin C-F. Noise and signal estimation in magnitude MRI and Rician distributed images: a LMMSE approach. IEEE Transactions on Image Processing. 2008;17(8):1383–1398
  2. Aja-Fernández S, Niethammer M, Kubicki M, Shenton ME, Westin C-F. Restoration of DWI data using a Rician LMMSE estimator. IEEE Transactions on Medical Imaging. 2008;27(10):1389–1403
  3. Basser PJ, Mattiello J, Lebihan D. MR diffusion tensor spectroscopy and imaging. Biophysial Journal. 1994;66(1):259–267
  4. Basser PJ, Pajevic S. Statistical artifacts in diffusion tensor MRI (DT-MRI) caused by background noise. Magnetic Resonance in Medicine. 2000;44:41–50
  5. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by Quantitative-Diffusion-Tensor MRI. Journal of Magnetic Resonance. 1996;111(3):209–219
  6. Basu S, Fletcher T, Whitaker R. Rician noise removal in diffusion tensor MRI. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science. vol. 1:Springer-Verlag; 2006;pp. 117–125
  7. Buades A, Coll B, Morel J. A review of image denoising algorithms, with a new one. Multiscale Modeling and Simulation. 2005;4(2):490–530
  8. Castaño-Moraga C, Lenglet C, Deriche R, Ruiz-Alzola J. A Riemannian approach to anisotropic filtering of tensor fields. Signal Processing. 2007;87(2):263–276
  9. Chen B, Hsu EW. Noise removal in magnetic resonance diffusion tensor imaging. Magnetic Resonance in Medicine. 2005;54:393–407
  10. Clarke RA, Scifo P, Rizzo G, Dell’Acqua F, Scotti G, Fazio F. Noise correction on Rician distributed data for fibre orientation estimators. IEEE Transactions on Medical Imaging. 2008;27(9):1242–1251
  11. Collins D, Zijdenbos A, Kollokian V, Sled J, Kabani N, Holmes C, et al. Design and construction of a realistic digital brain phantom. IEEE Transactions on Medical Imaging. 1998;17(3):463–468
  12. Coulon O, Alexander D, Arridge S. Diffusion tensor magnetic resonance image regularization. Medical Image Analysis. 2004;8(1):47–67
  13. Coupé P, Yger P, Prima S, Hellier P, Kervrann C, Barillot C. An optimized blockwise non local means denoising filter for 3D magnetic resonance images. IEEE Transactions on Medical Imaging. 2008;27(4):425–441
  14. Descotaux M, Wiest-Daesslé N, Prima S, Barillot C, Deriche R. Impact of Rician adapted Non-Local Means filtering on HARDI. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science. vol. 5242:Springer-Verlag; 2008;p. 122–130
  15. Descoteaux M, Angelino E, Fitzgibbons S, Deriche R. Apparent diffusion profile estimation from high angular resolution diffusion images: estimation and applications. Magnetic Resonance in Medicine. 2006;56(2):395–410
  16. Descoteaux M, Angelino E, Fitzgibbons S, Deriche R. Regularized, fast, and robust analytical Q-Ball imaging. Magnetic Resonance in Medicine. 2007;58:497–510
  17. Drumheller D. General expressions for Rician density and distribution functions. IEEE Transactions on Aerospace and Electronic Systems. 1993;29(2):580–588
  18. Fillard P, Pennec X, Arsigny V, Ayache N. Clinical DT-MRI estimation, smoothing, and fiber tracking with log-euclidean metrics. IEEE Transactions on Medical Imaging. 2007;26(11):1472–1482
  19. Gerig G, Kübler O, Kikinis R, Jolesz F. Nonlinear anisotropic filtering of MRI data. IEEE Transactions on Medical Imaging. 1992;11(2):221–232
  20. Gudbjartsson H, Patz S. The Rician distribution of noisy MRI data. Magnetic Resonance in Medicine. 1995;34:910–914
  21. Ibañez, L., Schroeder, W., Ng, L., Cates, J., 2005. The ITK Software Guide, second ed. Kitware Inc. ISBN 1-930934-15-7. <http://www.itk.org/ItkSoftwareGuide.pdf>.
  22. Jansons KM, Alexander DC. Persistent Angular Structures: new insights from diffusion magnetic resonance imaging data. Inverse Problems. 2003;19:1031–1046
  23. Jones DK, Basser PJ. Squashing peanuts and smashing pumpkins: how noise distorts diffusion weighted MR data. Magnetic Resonance in Medicine. 2004;52:979–993
  24. Kay SM. Fundamentals of statistical signal processing. Estimation Theory. Upper Saddle River, NJ 07458: Prentice-Hall; 1993;
  25. LeBihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161(2):401–407
  26. Manjón JV, Carbonell-Caballero J, Lull JJ, García-Martí G, Martí-Bonmatí L, Robles M. MRI denoising using Non-Local Means. Medical Image Analysis. 2008;12:514–523
  27. Martín-Fernández M, Alberola-López C, Ruiz-Alzola J, Westin C-F. Sequential anisotropic Wiener filtering applied to 3D MRI data. Magnetic Resonance in Medicine. 2007;25:278–292
  28. Martín-Fernández M, Muñoz-Moreno E, Cammoun L, Thiran J-P, Westin C-F, Alberola-López C. Sequential anisotropic multichannel Wiener filtering with Rician bias correction applied to 3D regularization of DWI data. Medical Image Analysis. 2009;13:19–35
  29. Marzetta, T., 1995. EM algorithm for estimating the parameters of multivariate complex Rician density for polarimetric SAR. In: Proceedings of ICASSP, vol. 5, pp. 3651–3654.
  30. McGibney G, Smith M. Unbiased signal to noise ratio measure for magnetic resonance images. Medical Physics. 1993;20(4):1077–1078
  31. Mori S, Wakana S, Nagae-Poetscher LM, van Zijl PC. MRI Atlas of Human White Matter. Amsterdam, The Netherlands: Elsevier; 2005;
  32. Netsch T, van Muiswinkel A. Quantitative evaluation of image-based distortion correction in Diffusion Tensor Imaging. IEEE Transactions on Medical Imaging. 2004;23(7):789–798
  33. Nowak R. Wavelet-based Rician noise removal for Magnetic Resonance Imaging. IEEE Transactions on Image Processing. 1999;8(10):108–1419
  34. Otsu N. A threshold selection method from gray-level histogram. IEEE Transactions on Systems, Man, and Cybernetics. 1979;9:62–66
  35. Özarslan E, Sepherd TM, Vemuri BC, Blackband SJ, Mareci TH. Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT). NeuroImage. 2006;31:1086–1103
  36. Özarslan E, Vemuri BC, Mareci TH. Generalized scalar measures for diffusion MRI using trace, variance and entropy. Journal of Magnetic Resonance in Medicine. 2005;53:866–876
  37. Pižurica A, Philips W, Lemahieu I, Acheroy M. A versatile Wavelet domain noise filtration technique for medical imaging. IEEE Transactions on Medical Imaging. 2003;22(3):323–331
  38. Poupon C, Clark CA, Frouin V, Rgis J, Bloch I, Bihan DL, et al. Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles. NeuroImage. 2000;12(2):184–195
  39. Salvador R, Pea A, Menon D-K, Carpenter T-A, Pickard J-D, Bullmore E-T. Formal characterization and extension of the linearized diffusion tensor model. Human Brain Mapping. 2005;24:144–155
  40. Sijbers J, den Dekker A-J. Maximum Likelihood estimation of signal amplitude and noise variance from MR data. Magnetic Resonance Imaging. 2004;51:586–594
  41. Sijbers J, Poot D, den Dekker A-J, Pintjenst W. Automatic estimation of the noise variance from the histogram of a magnetic resonance image. Physics in Medicine and Biology. 2007;52:1335–1348
  42. Tournier J-D, Calamante F, Connelly A. Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super–resolved spherical deconvolution. NeuroImage. 2007;35:1459–1472
  43. Tristán-Vega A, Aja-Fernández S. Joint LMMSE estimation of DWI data for DTI processing. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science. vol. 5242:Springer-Verlag; 2008;p. 27–34
  44. Tristán-Vega A, Aja-Fernández S. Design and construction of a realistic DWI phantom for filtering performance assessment. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science. vol. 5761:Springer–Verlag; 2009;p. 951–958
  45. Wang Z, Bovik A-C, Sheikh H-R, Simoncelli E-P. Image quality assessment: form error visibility to structural similarity. IEEE Transactions on Image Processing. 2004;13(4):600–612
  46. Wang Z, Vemuri B, Chen Y, Mareci TH. A constrained variational principle for direct estimation and smoothing of the diffusion tensor field from complex DWI. IEEE Transactions on Medical Imaging. 2004;23(8):930–939
  47. Wiest-Daesslé N, Prima S, Coupé P, Morrissey S, Barillot C. Non-local means variants for denoising of diffusion-weighted and diffusion tensor MRI. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science. vol. 4792:Springer-Verlag; 2007;p. 344–351
  48. Wiest-Daesslé N, Prima S, Coupé P, Morrissey S, Barillot C. Rician noise removal by Non-Local Means filtering for low signal-to-noise ratio MRI: applications to DT–MRI. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science. vol. 5242:Springer-Verlag; 2008;p. 171–179

PII: S1361-8415(09)00138-8

doi: 10.1016/j.media.2009.11.001

Medical Image Analysis
Volume 14, Issue 2 , Pages 205-218 , April 2010