Shisong Zhu
School of Computer Science and Technology, Henan Polytechnic University, Henan, Jiaozuo, 454003, China
Bibo Lu
School of Computer Science and Technology, Henan Polytechnic University, Henan, Jiaozuo, 454003, China
Cuiyun Zhang
School of Computer Science and Technology, Henan Polytechnic University, Henan, Jiaozuo, 454003, China
ABSTRACT
Magnetic Resonance (MR) image have been widely used and plays an important role in a clinical diagnosis. We focus on the denoising of MR image with a new high order regularization model. Contrary to previous fourth order models, the proposed energy functional contains the first order derivatives as boundary detector. The corresponding Euler-Lagrange equation can adjust diffusion speed adaptive to the local structure. The experimental results on the MR image show the performance of the proposed method. The effect of varying the high order regularization parameter is also reported.
PDF References Citation
How to cite this article
Shisong Zhu, Bibo Lu and Cuiyun Zhang, 2013. High Order Regularization for Mr Image Denoising. Information Technology Journal, 12: 6481-6486.
DOI: 10.3923/itj.2013.6481.6486
URL: https://scialert.net/abstract/?doi=itj.2013.6481.6486
DOI: 10.3923/itj.2013.6481.6486
URL: https://scialert.net/abstract/?doi=itj.2013.6481.6486
REFERENCES
- Awate, S.P. and R.T. Whitaker, 2007. Feature-preserving MRI denoising: A nonparametric empirical bayes approach. IEEE Trans. Med. Imaging, 26: 1242-1255.
CrossRefPubMedDirect Link - Chan, T., A. Marquina and P. Mulet, 2000. High-order total variation-based image restoration. SIAM J. Scientific Comput., 22: 503-516.
CrossRefDirect Link - Chambolle, A. and P.L. Lions, 1997. Image recovery via total variation minimization and related problems. Numer. Math, 76: 167-188.
CrossRefDirect Link - Gerig, G., O. Kubler, R. Kikinis and F. Jolesz, 1992. Nonlinear anisotropic filtering of MRI data. IEEE Trans. Med. Imaging, 11: 221-232.
CrossRefDirect Link - Kim, S. and H. Lim, 2009. Fourth-order partial differential equations for effective image denoising. Electron. J. Different. Equat., 17: 107-121.
Direct Link - Krissian, K. and S. Aja-Fernandez, 2009. Noise-driven anisotropic diffusion filtering of MRI. IEEE Trans. Med. Imaging, 18: 2265-2274.
CrossRefPubMedDirect Link - Lysaker, M., A. Lundervold and X.C. Tai, 2003. Noise removal using fourthorder partial differential equation with applications to medical magnetic resonance images in space and time. IEEE Trans. Image Process., 12: 1579-1590.
CrossRefDirect Link - Lysaker, M. and X.C. Tai, 2006. Iterative image restoration combining total variation minimization and a second-order functional. Int. J. Comput. Vision, 66: 5-18.
CrossRef - Ogier, A., P. Hellier and C. Barillot, 2006. Restoration of 3D medical images with total variation scheme on wavelet domains (TVW). Proceedings of the SPIE Medical Imaging: Image Processing, February 11-16, 2006, San Diego, USA., pp: 465-473.
Direct Link - Perona, P. and J. Malik, 1990. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell., 12: 629-639.
CrossRefDirect Link - Pizurica, A., W. Philips, I. Lemahieu and M. Acheroy, 2003. A versatile wavelet domain noise filtration technique for medical imaging. IEEE Trans. Med. Imag., 22: 323-331.
CrossRef - Rudin, L.I., S. Osher and E. Fatemi, 1992. Nonlinear total variation based noise removal algorithms. Physica D Nonlinear Phenomena, 60: 259-268.
Direct Link - Sapiro, G. and D.L. Ringach, 1996. Anisotropic diffusion of multivalued images with applications to color filtering. IEEE Trans. Image Process., 5: 1582-1586.
CrossRefDirect Link - Sijbers, J. and A.J. den Dekker, 2004. Maximum likelihood estimation of signal amplitude and noise variance from MR data. Magnet. Resonan. Med., 51: 586-594.
CrossRefPubMedDirect Link - Weaver, J.B., Y. Xu, D.M. Healy Jr. and L.D. Cromwell, 1991. Filtering noise from images with wavelet transforms. Magn. Resonance Med., 21: 288-295.
CrossRefPubMedDirect Link - Wood, J.C. and M.K. Johnson, 1999. Wavelet packet denoising of magnetic resonance images: Importance of Rician noise at low SNR. Magnet. Resonan. Med., 41: 631-635.
CrossRefPubMedDirect Link - You, Y.L. and M. Kaveh, 2000. Fourth-order partial differential equations for noise removal. IEEE Trans. Image Process., 9: 1723-1730.
CrossRefDirect Link - Zhu, W. and T. Chan, 2012. Image denoising using mean curvature of image surface. SIAM J. Imaging Sci., 5: 1-32.
CrossRefDirect Link