Coreg Datasets

We will demonstrate software for manual and automatic alignment of MRI volume FMRI images which provides improved speed, robustness and equivalent accuracy in comparison to commonly used techniques.
The automatic method has been designed for use on any data which has equivalent ordering of tissue grey level and has been acquired at approximately the same scale. This makes the technique applicable to a wide range of MR to MR alignment tasks. The statistical method maximises the normalised correlation between the x and y derivatives of three orthogonal projections from the data set. The algorithm is based on simplex optimisation which is generally acknowledged to be less sensitive to starting estimates of parameters than quasi-Newton techniques. The technique also computes the theoretical expected accuracy of alignment for each data set allowing an automatic test on performance.
The algorithm is more robust than conventional techniques [3] which can be directly attributed to being based on simplex optimisation. In particular it is far more resilient to large movements. The technique should also make possible the alignment of data sets which have large areas of structural changes by aligning using data away from the affected regions.
Once co-registered data sets can be rapidly re-sliced using re-normalised Sinc interpolation [1,2], which offers computational savings of between 7 and 30 over conventional techniques [4].

Library toolkit
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Sun Sparc - Solaris 2
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Intel x86 - Linux 2
[1] N.A.Thacker, A.Jackson, D.Moriarty and B.Vokurka, `Renormalised SINC Interpolation', proc. MIUA, Leeds, 33-37, 1998.
[2] N.A.Thacker, A.Jackson, D.Moriarty, B.Vokurka, `Improved Quality of Re-sliced MR Images Using Re-normalised Sinc Interpolation.' JMRI, 10, 4, 582-588, 1999.
Relevant other work
[3] R.P.Woods, J.C.Mazziotta and S.R.Cherry, `MRI-PET Registration with an Automated Algorithm.'JCAT, 17, 536-546, 1993.
[4] J.V.Hajnal, N.Saeed, E.J.Soar, A.Oatridge, I.R.Young and G.M.Bydder, `A Registration and Interpolation Procedure for Subvoxel Matching of Serially Acquired MR Images', Jou. Comp. Ass. Tom.,19(2), pp 289-296,1995.
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