CLC number: TP391
On-line Access:
Received: 2005-08-05
Revision Accepted: 2006-03-28
Crosschecked: 0000-00-00
Cited: 0
Clicked: 5974
GUO Qiang, YANG Xin. An edge-preserving algorithm of joint image restoration and volume reconstruction for rotation-scanning 4D echocardiographic images[J]. Journal of Zhejiang University Science A, 2006, 7(6): 960-968.
@article{title="An edge-preserving algorithm of joint image restoration and volume reconstruction for rotation-scanning 4D echocardiographic images",
author="GUO Qiang, YANG Xin",
journal="Journal of Zhejiang University Science A",
volume="7",
number="6",
pages="960-968",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A0960"
}
%0 Journal Article
%T An edge-preserving algorithm of joint image restoration and volume reconstruction for rotation-scanning 4D echocardiographic images
%A GUO Qiang
%A YANG Xin
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 6
%P 960-968
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A0960
TY - JOUR
T1 - An edge-preserving algorithm of joint image restoration and volume reconstruction for rotation-scanning 4D echocardiographic images
A1 - GUO Qiang
A1 - YANG Xin
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 6
SP - 960
EP - 968
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A0960
Abstract: A statistical algorithm for the reconstruction from time sequence echocardiographic images is proposed in this paper. The ability to jointly restore the images and reconstruct the 3D images without blurring the boundary is the main innovation of this algorithm. First, a Bayesian model based on MAP-MRF is used to reconstruct 3D volume, and extended to deal with the images acquired by rotation scanning method. Then, the spatiotemporal nature of ultrasound images is taken into account for the parameter of energy function, which makes this statistical model anisotropic. Hence not only can this method reconstruct 3D ultrasound images, but also remove the speckle noise anisotropically. Finally, we illustrate the experiments of our method on the synthetic and medical images and compare it with the isotropic reconstruction method.
[1] Besag, J., 1986. On the statistical analysis of dirty pictures. J. Roy. Statist. Soc., Ser.B, 48(3):259-302.
[2] Cardinal, H.N., Gill, J., Fenster, A., 2000. Analysis of geometrical distortion and statistical variance in length, area and volume in a linearly scanned 3D ultrasound image. IEEE Trans. Med. Imaging, 19(6):632-651.
[3] Corsine, G., Mossa, A., Verrazzani, L., 1996. Signal-to-noise ratio and autocorrelation function of the image intensity in coherent systems: sub-Rayleigh and super-Rayleigh conditions. IEEE Trans. Image Process, 5(1):132-141.
[4] Duann, J.R., Lin, S.B., Hu, W.C., Su, J.L., 1999. Computer system for four-dimensional transesophageal echocardiographic image reconstruction. Computerized Medical Imaging and Graphics, 23(4):173-179.
[5] Fenster, A., Downey, D.B., Cardinal, H.N., 2001. Three-dimensional ultrasound imaging. Phys. Med. Biol., 46(5):67-99.
[6] German, S., German, D., 1984. Stochastic relaxation, gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Analysis and Machine Intelligence, 6:721-741.
[7] Ghosh, A., Nanda, N.C., Maurer, G., 1982. Three-dimensional reconstruction of echocardiographic images using the rotation method. Ultrasound in Med. & Bio., 8(6):655-657.
[8] Li, S.Z., 2001. Markov Random Field Modeling in Computer Vision, 2nd Ed. Springer-Verlag, p.37-63.
[9] Ramponi, G., 1999. Warped distance for space-variant linear image interpolation. IEEE Trans. Image Processing, 8(5):629-639.
[10] Roelandt, Jos R.T.C., 2000. Three-dimensional echocardiography: the future today! Computers & Graphics, 24(5):715-729.
[11] Sanches, J.M., Marques, J.S., 2000. A Rayleigh reconstruction/interpolation algorithm for 3D ultrasound. Pattern Recognition Letter, 21(10):917-926.
[12] Sanches, J.M., Marques, J.S., 2001. A fast MAP Algorithm for 3D Ultrasound. EMMCVPR 2001, p.63-74.
[13] Sanches, J.M., Marques, J.S., 2002. A multiscale algorithm for three-dimensional free-hand ultrasound. Ultrasound Med. & Biol., 28(8):1029-1040.
[14] Sanches, J.M., Marques, J.S., 2003. Joint image registration and volume reconstruction for 3D ultrasound. Pattern Recognition Letter, 24(4-5):791-800.
[15] Shankar, P., 1986. Speckle reduction in ultrasound B-scans using weighted averaging in spatial compounding. IEEE Trans. Ultrasonic, Ferroelectrics and Frequency Control, 33(6):754-758.
[16] Tsai, C.J., Hung, Y.P., Hsu, S.C., 1993. Comparison between Asymptotic Bayesian Approach and Kalman Filter-Based Technique for 3D Reconstruction Using an Image Sequence. CVPR, p.206-211.
[17] Tong, S., Downey, D.B., Cardinal, H.N., Fenster, A., 1996. A three-dimensional ultrasound prostate imaging system. Ultrasound Med. & Biol., 22(6):735-746.
[18] Tong, S., Cardinal, H.N., Downey, D.B., Fenster, A., 1998. Analysis of linear, area and volume distortion in 3D ultrasound imaging. Ultrasound Med. & Biol., 24(3):355-373.
[19] Treece, G.M., Prager, R.W., Gee, A.H., Berman, L., 2001. Correction of Probe Pressure Artifacts in Freehand 3D Ultrasound. Proceeding of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2001), p.283-290.
[20] Weickert, J., 1998. Anisotropic diffusion in image processing. Teubner Verlag, p.54-107.
Open peer comments: Debate/Discuss/Question/Opinion
<1>