Spatial based polynomial 2D-warping-a possibility to reduce interindividual variations in functional neuroimaging?

As an approach to reduce the variation in functional brain images between different individuals we tested different methods for an elastic image deformation by polynomial warping. The polynomials vary in degree and number and distribution of the grid-points. The computations show that image warping...

Full description

Saved in:
Bibliographic Details
Published inProceedings of 3rd IEEE International Conference on Image Processing Vol. 3; pp. 739 - 742 vol.3
Main Authors Lohmann, K., Staak, S., Gundelfinger, E.D., Hess, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Brain
Digital images
Distributed computing
Grid computing
Magnetic resonance imaging
Neuroimaging
Pixel
Polynomials
Shape
Testing
Online AccessGet full text

Cover

More Information
Summary:As an approach to reduce the variation in functional brain images between different individuals we tested different methods for an elastic image deformation by polynomial warping. The polynomials vary in degree and number and distribution of the grid-points. The computations show that image warping with second degree polynomials and equally distributed grid-points increases most efficiently the similarity of shape and gray-values in the images whereas the tested higher degree polynomials are not useful.
ISBN:9780780332591
0780332598
DOI:10.1109/ICIP.1996.560801