PDF
Abstract
Three-dimensional (3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance (MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.
Keywords
Mean Square Error
/
Wavelet Coefficient
/
Peak Signal Noise Ratio
/
Wavelet Domain
/
Triangle Mesh
Cite this article
Download citation ▾
De-xin Zhao, Peng-jie Liu, De-gan Zhang.
MR image denoising method for brain surface 3D modeling.
Optoelectronics Letters 477-480 DOI:10.1007/s11801-014-4105-8
| [1] |
Shyam AnandC, SahambiJ S. Magnetic Resonance Imaging, 2010, 28: 842
|
| [2] |
MohanJ, KrishnaveniV, GuoY. Biomedical Signal Processing and Control, 2013, 8: 779
|
| [3] |
ChenG, QianS E. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49: 973
|
| [4] |
ManjónJ V, CoupéP, Martí-BonmatíL, Louis CollinsD, RoblesM. Journal of Magnetic Resonance Imaging, 2010, 31: 192
|
| [5] |
RuikarS D, DoyeD D. International Journal of Advanced Computer Science and Applications, 2011, 2: 49
|
| [6] |
WangS, ZhouY, ZouD. Journal of Infrared and Millimeter Waves, 2001, 20: 387
|
| [7] |
KhareA, TiwaryU S, PedryczW. Imaging Science Journal, 2010, 58: 340
|
| [8] |
SendurL, SelesnickI W. IEEE Signal Processing Letters, 2002, 9: 438
|
| [9] |
RajanJ, PootD, JuntuJ, SijbersJ. Physics in Medicine and Biology, 2010, 55: 441
|
| [10] |
LuisierF, VoneschC, BluT, UnserM. Signal Processing, 2010, 90: 415
|
| [11] |
KhareA, KhareM, JeongY. Signal Processing, 2010, 90: 428
|
| [12] |
ZhangD, ZhangX. Enterprise Information Systems, 2012, 6: 473
|
| [13] |
ZhangD, LiG, ZhengK. IEEE Transaction on Industrial Informatics, 2014, 10: 766
|
| [14] |
ZhangD, KangX. Journal on Advances in Signal Processing, 2012, 110: 1
|
| [15] |
ZhangD-G, KangX-J, WangD. Journal of Optoelectronics·Laser, 2012, 23: 180
|
Just Accepted
This article has successfully passed peer review and final editorial review, and will soon enter typesetting, proofreading and other publishing processes. The currently displayed version is the accepted final manuscript. The officially published version will be updated with format, DOI and citation information upon launch. We recommend that you pay attention to subsequent journal notifications and preferentially cite the officially published version. Thank you for your support and cooperation.