Quantifying Small Changes in Brain Ventricular Volume Using Non-rigid Registration (original) (raw)

Abstract

Non-rigid registration can automatically quantify small changes in volume of anatomical structures over time by means of segmentation propagation. Here we use a non-rigid registration algorithm based on optimising normalised mutual information to quantify small changes in brain ventricular volume in MR images of a group of five patients treated with growth hormone replacement therapy and a control group of six volunteers. The lateral ventricles are segmented from each subject image by registering the brainweb image [1] which has this structure delineated. The mean (standard deviation) volume change measurements are 1.09cc (0.73cc) for the patient group and 0.08cc (0.62cc) for the volunteer group, this difference is statistically significant at the 1% level. We validate our volume change measurements by comparing them to previously published results obtained by visual inspection of difference images, and demonstrate high rank correlation coefficient (ρ = 0.7, n=11).

Chapter PDF

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

References

  1. D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, A. C. Evans: Design and construction of a realistic digital brain phantom. IEEE Trans on Medical Imaging 17 (1998) 463–468
    Article Google Scholar
  2. Bajcsy, R., Kovacic, S.: Multiresolution elastic matching. Computer Vision, Graphics and Image Processing 46 (1989) 1–21
    Article Google Scholar
  3. B. M. Dawant, S. L. Hartmann, J. P. Thirion, F. Maes, D. Vandermeulen, P. Demaerel: Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part I, methodology and validation on normal subjects. IEEE Trans on Medical Imaging 18 (1999) 909–916
    Article Google Scholar
  4. G. Calmon, N. Roberts: Automatic measurement of changes in brain volume on consecutive 3D MR images by segmentation propagation. Magnetic Resonance Imaging 18 (2000) 439–453
    Article Google Scholar
  5. D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, D. J. Hawkes: Non-rigid registration using free-form deformations: Application to breast MR Images. IEEE Trans on Medical Imaging 18 (1999) 712–721
    Article Google Scholar
  6. E. R. E. Denton, M. Holden, E. Christ, J.M. Jarosz, D. Russell-Jones, J. Goodey, T. C. S. Cox, D. L. G. Hill: The identification of cerebral volume changes in treated growthh ormone deficient patients using serial 3-D MR image processing. Journal of Computer Assisted Tomography 24 (2000) 139–145
    Article Google Scholar
  7. Schnabel, J.A., Tanner, C., Smith, A.C., Leach, M.O., Hayes, C., Degenhard, A., Hose, R., Hill, D.L.G., Hawkes, D.J.: Validation of non-rigid registration using Finite Element Methods. In: Proc. 17th Int. IPMI 2001 Conf. Vol LNCS 2082, Springer Verlag (2001) 344–357
    Google Scholar
  8. C. Studholme, D. L. G. Hill, D. J. Hawkes: Automated three-dimensional registration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. Medical Physics 24 (1997) 25–35
    Article Google Scholar
  9. M. Bland: An introduction to medical statistics. Oxford Medical Publications (1995) ISBN: 0-19-262428-8.
    Google Scholar
  10. G. E. Christensen, R. D. Rabbitt and M. I. Miller: Deformable templates using large deformation kinematics. IEEE Trans on Image Processing 5 (1996) 1435–1447
    Article Google Scholar
  11. J.-P. Thirion: Image matching as a diffusion process: an analogy with Maxwell’s demons. Medical Image Analysis 2 (1998) 243–260
    Article Google Scholar

Download references

Author information

Authors and Affiliations

  1. Computational Imaging Science Group, Division of Radiological Sciences and Medical Engineering, Guy’s, King’s and St. Thomas’ School of Medicine, Guy’s Hospital, King’s College, London, UK
    Mark Holden, Julia A. Schnabel & Derek L. G. Hill

Authors

  1. Mark Holden
  2. Julia A. Schnabel
  3. Derek L. G. Hill

Editor information

Editors and Affiliations

  1. Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
    Wiro J. Niessen & Max A. Viergever &

Rights and permissions

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Holden, M., Schnabel, J.A., Hill, D.L.G. (2001). Quantifying Small Changes in Brain Ventricular Volume Using Non-rigid Registration. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3\_7

Download citation

Keywords

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.

Publish with us