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Simulation of Acquisition Artefacts in MR Scans: Effects on Automatic Measures of Brain Atrophy

  • Oscar Camara-Rey
  • Beatrix I. Sneller
  • Gerard R. Ridgway
  • Ellen Garde
  • Nick C. Fox
  • Derek L. G. Hill
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

Automatic algorithms in conjunction with longitudinal MR brain images can be used to measure cerebral atrophy, which is particularly pronounced in several types of dementia. An atrophy simulation technique has been devised to facilitate validation of these algorithms. To make this model of atrophy more realistic we simulate acquisition artefacts which are common problems in dementia imaging: motion (both step and periodic motion) and pulsatile flow artefact. Artefacts were simulated by combining different portions of k-space from various modified image. The original images were 7 MR scans of healthy elderly controls, each of which had two levels of simulated atrophy. We investigate the effect of the simulated acquisition artefacts in atrophy measurements provided by an automatic technique, SIENA.

Keywords

Simulated Image Serial Magnetic Resonance Imaging Atrophy Rate Flow Artefact Healthy Elderly Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Freeborough, P., Fox, N.: The boundary shift integral: an accurate and robust measure of cerebral volume changes from registered repeat MRI. IEEE Transactions on Medical Imaging 16, 623–629 (1997)CrossRefGoogle Scholar
  2. 2.
    Smith, S., Stefano, N.D., Jenkinson, M., Matthews, P.: Normalized accurate measurement of longitudinal brain change. Journal of Computer Assisted Tomography 25, 466–475 (2001)CrossRefGoogle Scholar
  3. 3.
    Davatzikos, C., Genc, A., Xu, D., Resnick, S.: Voxel-based Morphometry using the RAVENS maps: methods and validation using simulated longitudinal atrophy. Neuroimage 14, 1361–1369 (2001)CrossRefGoogle Scholar
  4. 4.
    Freeborough, P., Fox, N., Kitney, R.: Modeling brain deformations in Alzheimer’s disease by fluid registration of serial 3D MR Images. Journal of Computer Assisted Tomography 22, 838–843 (1998)CrossRefGoogle Scholar
  5. 5.
    Camara, O., Schweiger, M., Scahill, R.I., Crum, W.R., Sneller, B.I., Schnabel, J.A., Ridgway, G.R., Cash, D.M., Hill, D.L.G., Fox, N.C.: Phenomenological model of diffuse global and regional atrophy using Finite-Element methods. IEEE Transactions on Medical Imaging (in press, 2006)Google Scholar
  6. 6.
    Howarth, C., Hutton, C., Deichmann, R.: Improvement of the image quality of T1-weighted anatomical brain scans. Neuroimage 29, 930–937 (2005)CrossRefGoogle Scholar
  7. 7.
    Atkinson, D., Hill, D.L., Stoyle, P.N., Summers, P.E., Clare, S., Bowtell, R., Keevil, S.F.: Automatic compensation of motion artifacts in MRI. Magnetic Resonance Medicine 41, 163–170 (1999)CrossRefGoogle Scholar
  8. 8.
    Manduca, A., McGee, K.P., Welch, E.B., Felmlee, J.P., Grimm, R.C., Ehman, R.L.: Autocorrection in MR imaging: adaptive motion correction without navigator echoes. Radiology 215, 904–909 (2000)Google Scholar
  9. 9.
    Blumenthal, J.D., Zijdenbos, A.l., Molloy, E., Giedd, J.N.: Motion artifact in magnetic resonance imaging: implications for automated analysis. Neuroimage 16, 89–92 (2002)CrossRefGoogle Scholar
  10. 10.
    Preboske, G.M., Gunter, J.L., Ward, C.P., Jack Jr., C.R.: Common MRI acquisition non-idealities significantly impact the output of the boundary shift integral method of measuring brain atrophy on serial MRI. Neuroimage (in press, 2006)Google Scholar
  11. 11.
    Holdsworth, D., Norley, C., Frayne, R., Steinman, D., Rutt, B.: Characterization of common carotid artery blood-flow waveforms in normal human subjects. Physiological Measurement 20, 219–240 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Oscar Camara-Rey
    • 1
  • Beatrix I. Sneller
    • 1
  • Gerard R. Ridgway
    • 1
  • Ellen Garde
    • 2
  • Nick C. Fox
    • 2
  • Derek L. G. Hill
    • 1
  1. 1.Center of Medical Image ComputingUniversity College of LondonUK
  2. 2.Dementia Research Centre, Institute of NeurologyUniversity College Of LondonUK

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