Information in magnetic resonance images: evaluation of signal, noise and contrast

  • J. P. De Wilde
  • J. A. Lunt
  • K. Straughan


The assessment of diagnostic image quality for MRI is considered. The assessment of three key image quality determinants is addressed: signal, noise and contrast. There is a distinction between random noise evaluation, for the calculation of the SNR, and structured noise evaluation for the assessment of image artefacts. Specific methods used are correlation techniques and the Wiener spectrum. Contrast is assessed by comparison of experimental data and theoretical predictions. For each assessment, the theory and method of the evaluation strategy are discussed. The discussion is illustrated with analysis results from commercial MR systems. The choice of analysis method and the subsequent derivation of quality indices are shown to be critical in respect of robustness and accuracy.


Contrast-to-noise Correlation Ghosting artefacts Image quality Magnetic resonance imaging Signal-to-noise ratio Wiener spectrum 


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  1. Bydder, G. M. (1988): ‘Magnetic resonance imaging: present status and future perspectives’,Br. J. Radiol.,61, (730), pp. 889–897CrossRefGoogle Scholar
  2. Dainty, J. C., andShaw, R. (1974): ‘Image science’, (Academic Press, London) p. 222Google Scholar
  3. Edelstein, W. A., Bottomley, P. A., andPfeifer, L. M. (1984): ‘A SIGNAL-TO-NOISE CALIBRATION PROCEDURE FOR NMR IMAGING SYSTEMS,’med. phys.,11,(2), PP. 180–236CrossRefGoogle Scholar
  4. Farrar, T. C., andBecker, E. D. (1971): ‘Pulse and Fourier transform NMR’, (Academic Press, London) pp. 7–8Google Scholar
  5. Hendrick, R. E., Nelson, T. R., andHendee, W. R. (1984): ‘Phase detection and contrast loss in magnetic resonance imaging’,Magn. Reson. Imaging,2, pp. 279–283CrossRefGoogle Scholar
  6. Knowles, R. J. R., andMarkisz, J. A. (1988): ‘Quality assurance and image artifacts in magnetic resonance imaging.’ (Little Brown and Company)Google Scholar
  7. Lerski, R. A. andDe Certaines, J. D. (1993): ‘Performance assessment and quality control in MRI by Eurospin test objects and protocols’,Magnet. Reson. Imaging,11, pp. 817–833CrossRefGoogle Scholar
  8. Lerski, R. A., Lunt, J. A., andBean, J. P. (1992): ‘Quality control in magnetic resonance imaging’,RAD Mag.,18, (206), pp. 19–21Google Scholar
  9. Lerski, R. A., McRobbe, D. W., Straughan, K., Walker, P. M., De Certaines, J. D., andBernard, A. M. (1988): ‘Multi-center trial with protocols and prototype test objects for the assessment of MRI equipment’,Magnet. Reson. Imaging,6, pp. 201–214CrossRefGoogle Scholar
  10. Lerski, R. A., Straughan, K., andWilliams, J. L. (1986): ‘Practical aspects of ghosting in resistive nuclear magnetic resonance imaging systems’,Phys. Med. Biol,31, pp. 721–735CrossRefGoogle Scholar
  11. Nelson, T. R., Hendrick, R. E., andHendee, W. R. (1984): ‘Selection of pulse sequences producing maximum tissue contrast in magnetic resonance imaging’,Magnet. Reson. Imaging,2, pp. 285–294CrossRefGoogle Scholar
  12. Nema (1988): ‘Determination of signal-to-noise ratio (SNR) in diagnostic magnetic resonance images’. Document MS 1, National Electrical Manufacturers Association, 2101 L Street, N.W. Washington, DC 20037, USAGoogle Scholar
  13. Nema (1989a): ‘Determination of two dimensional geometric distortion in diagnostic magnetic resonance images’.Document MS 2, National Electrical Manufacturers Association, 2101 L Street, N.W. Washington, DC 20037, USAGoogle Scholar
  14. Nema (1989b): ‘Determination of image uniformity in diagnostic magnetic resonance images’. Document MS 3, National Electrical Manufacturers Association, 2101 L Street, N.W. Washington, DC 20037, USAGoogle Scholar
  15. Nema (1989c): ‘Acoustic noise measurement procedure for diagnostic magnetic resonance images,’ Document MS 4, National Electrical Manufacturers Association, 2101 L Street N.W. Washington, DC 20037, USAGoogle Scholar
  16. Och, I. G., Clarke, G. D., Sobol, W. T., Rosen, C. W., andMun, S. K. (1992): ‘Acceptance testing of magnetic resonance imaging systems: Report of AAPM nuclear magnetic resonance’,Med. Phys.,19, (1), pp. 217–229CrossRefGoogle Scholar
  17. Ortendahl, D. A., Crooks, L. E., andKaufman, L. (1983): ‘A comparison of the noise characteristics of projection reconstruction and two dimensional fourier transforms in NMR Imaging’,IEEE Trans. NS-30 (1), pp. 692–696Google Scholar
  18. Press, W. H., Flannery, B. P., Teukolsky, S. A., andVetterling, W. T. (1988): ‘Numerical recipes in C’. (Cambridge University Press, Cambridge) pp. 400–401MATHGoogle Scholar
  19. Price, R. R., Axel, L., Morgan, T., Newman, R., Perman, W., Schneiders, N., Selikson, M., Wood, M., andThomas, S. R. (1990): ‘Quality assurance methods and phantoms for magnetic resonance imaging: report of AAPM nuclear magnetic resonance task group no. 1a’,Med. Phys.,17, (2), pp. 287–295CrossRefGoogle Scholar
  20. Rosen, B. R., Pykett, I. L. andBrady, T. J. (1984): ‘Spin lattice relaxation time measurements in two-dimensional nuclear magnetic resonance imaging: corrections for plane selection and pulse sequence’,J. Comput. Assit. Tomogr.,8, (2), pp. 195–199Google Scholar
  21. UKDepartment of Health (1990–1996): ‘MDA reports on the assessment of the imaging performance of MR Imaging Systems.’ DH (Leaflets) PO Box 21, Stanmore, Middlesex, HA7 1AY, UKGoogle Scholar
  22. Wehrli, F. W., Shaw, D., andKneeland, J. B. (1991): ‘Biomedical magnetic resonance imaging: principles, methodology, and applications’, (VCH Publishers, New York) pp. 47–112Google Scholar

Copyright information

© IFMBE 1997

Authors and Affiliations

  • J. P. De Wilde
    • 1
  • J. A. Lunt
    • 2
  • K. Straughan
    • 1
  1. 1.Department of Electrical and Electronic EngineeringImperial CollegeLondonUK
  2. 2.Department of Health LondonMedical Devices AgencyUK

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