Biomedical Engineering Reference
In-Depth Information
Figure 6.7:
Five corresponding image slices from MRI acquired brains with
manually identified points of correspondence.
(CLI-TPS) thin-plate spline algorithms. These 256
×
320 pixel images with 1 mm
isotropic pixel dimension were extracted from 3D MRI data sets such that they
roughly corresponded to one another. Each data set was registered with the
other four data sets for each of the four algorithms producing 10 forward and
reverse transformations for each algorithm. For brevity of presentation, we only
present some of the results of the experiments that are representative of all of
the results. A set 39 of the corresponding landmarks were manually defined in
data sets
B
2 and
B
4 and a subset of the 39 landmarks were manually defined
in the additional three datasets (see Fig. 6.7). Only data sets B2 and B4 had all
39 landmarks identified on them since it was not possible to locate the corre-
sponding locations for all the landmarks on the other data sets due to missing
or different shaped sulci. Only corresponding landmarks between two images
were used for registration and calculating the landmark error, i.e., if one image
set was missing landmark 15, then landmark 15 was not used for registration or
for calculating the landmark error.
The result of transforming MRI data set
B
5 in to the shape of
B
2 using each
of the four registration algorithms is shown in Fig. 6.8. These results are typical
of the other pairwise registration combinations. The images are arranged left to
right from the worst to the best similarity match as shown by the corresponding
difference images shown below the transformed images. The UL-TPS and CL-
TPS algorithms perform almost identically with respect to similarity matching.
The CI-TPS and CLI-TPS intensity based registrations produce better similarity
match than the two landmark only methods. In particular, the intensity based
methods match the border locations and non-landmark locations better than
the landmark thin-plate spline or CL-TPS algorithms. The difference between
the CI-TPS and CLI-TPS methods is that the CLI-TPS method produces much
