Next: Introduction
Optimisation in Robust Linear Registration of
Brain Images
FMRIB Technical Report TR00MJ2
(A related paper has been submitted to Medical Image Analysis)
Mark Jenkinson and Stephen Smith
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB),
Department of Clinical Neurology, University of Oxford, John Radcliffe Hospital,
Headley Way, Headington, Oxford, UK
Abstract:
Registration is an important component of medical image analysis and
for analysing large amounts of data it is desirable to have fully
automatic registration methods. Many different automatic registration
methods have been proposed to date, and almost all share a common
mathematical framework -- one of optimising a cost function. To date
little attention has been focused on the optimisation method itself, as
opposed to other aspects of the problem like defining suitable cost
functions. However, the success of most registration methods hinges
on optimisation method.
This report examines the assumptions underlying the registration
problem and shows that the use of local optimisation methods together
with the standard multi-resolution approach is
not sufficient
to reliably find the global minimum. In addition, a global
optimisation method is proposed that is specifically tailored to this
registration problem. A full discussion of all the necessary
implementation details is included as this forms an important aspect
of any practical method. Furthermore, results are presented that show
that the proposed method is more reliable at finding the global
minimum than several of the currently available registration packages
in common usage.
Keywords: affine transformation, global optimisation, multimodal
registration, multi-resolution search, robustness
Next: Introduction
Mark Jenkinson
2000-05-10