Voxel Similarity Measures for 3D Serial MR Brain Image Registration


from: 16-th International Conference on Information Processing in Medical Imaging pp. 472-477 (June, 1999)

Mark Holden, Derek L.G. Hill, Erika R. E. Denton¹ Jo M. Jarosz¹ Tim C. S. Cox² and David J. Hawkes

Radiological Sciences, GKT, Guy's Hospital, London, SE1 9RT, UK.

¹ Radiology Dept., King's College Hospital, London SE5 9RS, UK

² Institute of Neurology, UCL, Queen's Square, London WC1N 3BG, UK

e-mail: mark.holden@kcl.ac.uk

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.


This paper is available from Medline or the pdf.
Mark Holden Radiological Sciences.
Email: mark.holden@kcl.ac.uk Last modified: 4 May, 2001.