Voxel Similarity Measures for 3D Serial MR Brain Image Registration

  • Mark Holden
  • Derek L. G. Hill
  • Erika R. E. Denton
  • Jo M. Jarosz
  • Tim C. S. Cox
  • David J. Hawkes
Conference paper

DOI: 10.1007/3-540-48714-X_48

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1613)
Cite this paper as:
Holden M., Hill D.L.G., Denton E.R.E., Jarosz J.M., Cox T.C.S., Hawkes D.J. (1999) Voxel Similarity Measures for 3D Serial MR Brain Image Registration. In: Kuba A., Šáamal M., Todd-Pokropek A. (eds) Information Processing in Medical Imaging. IPMI 1999. Lecture Notes in Computer Science, vol 1613. Springer, Berlin, Heidelberg

Abstract

We investigated 7 different similarity measures for rigid body registration of serial MR brain scans. To assess their accuracy we used a set of 33 clinical 3D serial MR images, manually segmented by a radiologist to remove deformable extra-dural tissue, and also simulated brain model data. For each measure we determined the consistency of registration transformations for both sets of segmented and unsegmented data. The difference images produced by registration with and without segmentation were visually inspected by two radiologists in a blinded study. We have shown that of the measures tested, those based on joint entropy produced the best consistency and seemed least sensitive to the presence of extra-dural tissue. For this data the difference in accuracy of these joint entropy measures, with or without brain segmentation, was within the threshold of visually detectable change in the difference images.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Mark Holden
    • 1
  • Derek L. G. Hill
    • 1
  • Erika R. E. Denton
    • 2
  • Jo M. Jarosz
    • 2
  • Tim C. S. Cox
    • 3
  • David J. Hawkes
    • 1
  1. 1.Radiological Sciences and Biomedical Engineering. The Guy’s, King’s and St Thomas’ School of MedicineKing’s College LondonLondonUK
  2. 2.Radiology and Neuroimaging DeptsKing’s College HospitalLondon
  3. 3.Institute of NeurologyUCLLondon

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