Improved optimization strategies for autofocusing motion compensation in MRI via the analysis of image metric maps.

Abstract:

:Autofocusing is a postprocessing technique for motion correction, which optimizes an image quality metric against various trial motions. In this work, image metric maps, which are measures of image quality plotted as a function of in-plane 2-D trial translations, are systematically studied to develop improved autofocusing motion correction algorithms. It is shown that determining object motion with autofocusing is equivalent to an image metric map optimization problem. These maps provide insights into the motion compensation process and help improve several aspects of the correction algorithm, including the selection of the image metric and motion search strategy. A highly efficient and robust 2-D global optimization method is devised, exploiting the properties of the metric map pattern. The improved algorithm is used to correct phantom and clinical MR images with in-plane 2-D translational motion and is shown to be more effective than existing methods.

journal_name

Magn Reson Imaging

authors

Lin W,Song HK

doi

10.1016/j.mri.2006.02.003

subject

Has Abstract

pub_date

2006-07-01 00:00:00

pages

751-60

issue

6

eissn

0730-725X

issn

1873-5894

pii

S0730-725X(06)00144-5

journal_volume

24

pub_type

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