| Author(s) |
Julian Mattes
Johannes Gall
Alfredo Lopez
|
| Title |
A maximal mass confinement principle for rigid and locally rigid image registration |
| Booktitle |
Proc. MICCAI 2008 |
| Typ |
Inproceedings |
| Month |
September 2008 |
| Year |
2008 |
| Volume |
5242 |
| Serie |
Lecture Notes in Computer Science |
| Pages |
1058-1065 |
| Editor(s) |
Metaxas, D.; Axel, L.; Fichtinger, G.; Szekely, G. |
| Publisher |
Springer |
| ISBN |
978-3-540-85989-5 |
| SCCH # |
0825 |
| In this paper we propose (1) to set the problem of image registration
as a contour/region-template-to-image matching problem using
so-called confiners – also called blobs or components – as template regions,
(2) to select the confiners of one of the images by passing through
the hierarchical structure which they define and registering them successively
rigidly form coarse-to-fine to the other image, the target image,
and (3) we propose a maximum mass confinement (MMC) principle for
contour-to-image registration. This principle allows us to derive a similarity
measure assessing how well the confiner fits into the target image
simply by calculating the gray value mass confined by its contour. By
optimizing this measure for rigid transformations we obtain our MMC
algorithm registering a contour locally rigid to the target image. We illustrate
that by proceeding based on (1-3) problems can be avoided which
were related to previous registration algorithms based on confiners. We
compare our MMC algorithm with another template matching algorithm
based on normalized mutual information. Equally, we compare our hierarchical
image registration strategy with B-Spline based non-rigid registration
using normalized mutual information. We performed our evaluation
on real and simulated images in terms of robustness, accuracy
and computation speed. We show that both, MMC template matching
on its own and hierarchical image registration using MMC, in most cases
outperform the respective alternative method. |