MR image denoising method for brain surface 3D modeling

De-xin Zhao , Peng-jie Liu , De-gan Zhang

Optoelectronics Letters ›› : 477 -480.

PDF
Optoelectronics Letters ›› : 477 -480. DOI: 10.1007/s11801-014-4105-8
Article

MR image denoising method for brain surface 3D modeling

Author information +
History +
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

登录浏览全文

4963

注册一个新账户 忘记密码

References

[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

AI Summary AI Mindmap
PDF

74

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/