MODIFIED ITERATIVE MODEL BASED ON DATA EXTRAPOLATION METHOD TO REDUCE GIBBS RINGING

被引:19
作者
AMARTUR, S
HAACKE, EM
机构
[1] Department of Radiology, University Hospitals, Case Western Reserve University, Cleveland, Ohio
[2] Departments of Physics and Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
来源
JMRI-JOURNAL OF MAGNETIC RESONANCE IMAGING | 1991年 / 1卷 / 03期
关键词
ARTIFACT; IMAGE FILTERING; IMAGE PROCESSING; PHANTOMS; PHYSICS;
D O I
10.1002/jmri.1880010309
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
An iterative algorithm that involves image filtering and data replacement (as suggested by Constable and Henkelman) is investigated for reducing the Gibbs artifact in magnetic resonance imaging. The image is processed with an edge-preserving filter to estimate the height and location of a set of model elements (delta-functions or boxes) for generating the missing high-frequency information. Filtering was performed in the complex image domain to account for discontinuities in phase as well as magnitude. The process is repeated after each data replacement to handle varying degrees of contrast. The convergence and signal-to-noise characteristics of the algorithm are investigated by means of simulated and clinical examples. The results indicate that the algorithm performs reasonably well in reducing ringing artifacts due to nearby edge contrast seen in most of the homogeneous, isointense regions. Nevertheless, it may generate some spurious thickening of structures that do not match the assumed step-edge models.
引用
收藏
页码:307 / 317
页数:11
相关论文
共 15 条
  • [1] Bronskill MJ, McVeigh ER, Kucharczyk W, Henkelman RM, Syrinx‐like artifacts on MR images of the spinal cord, Radiology, 166, pp. 485-488, (1988)
  • [2] Levy LM, Chiro GD, Brooks RA, Dwyer AJ, Wener L, Frank J, Spinal cord artifacts from truncation errors during MR imaging, Radiology, 166, pp. 479-483, (1988)
  • [3] Fuderer M, Ringing artifact reduction by an efficient likelihood improvement method. Proc SPIE, Science and Engineering in Medical Imaging, Paris, 1137, pp. 84-90, (1989)
  • [4] Constable RT, Henkelman RM, Data extrapolation for Gibbs artifact removal, Magn Reson Med, 17, pp. 108-118, (1991)
  • [5] Hu X, Stillman AE, Technique for reduction of truncation artifact in chemical shift images (abstr), Book of abstracts: Society of Magnetic Resonance in Medicine 1990, (1990)
  • [6] Haacke EM, Liang Z, Izen S, Constrained reconstruction: a super‐resolution, optimal signal‐to‐noise alternative to the Fourier transform in magnetic resonance imaging, Med Phys, 16, pp. 388-397, (1989)
  • [7] Liang Z, Haacke EM, Thomas C, High‐resolution inversion of finite Fourier transform data through a localized polynomial approximation, Inverse Problems, 5, pp. 831-847, (1989)
  • [8] Martin JF, Tirendi CF, Modified linear prediction in magnetic resonance imaging, J Magn Reson, 82, pp. 392-399, (1989)
  • [9] Smith MR, Nichols ST, Henkelman RM, Wood ML, Application of autoregressive modeling in magnetic resonance imaging to remove noise and truncation artifacts, Magn Reson Imaging, 4, pp. 257-261, (1986)
  • [10] Smith MR, Nichols ST, A comparison of models used as alternative magnetic resonance image reconstruction methods, Magn Reson Imaging, 8, pp. 173-183, (1990)