Biomedical Engineering Reference
In-Depth Information
Figure 9.14:
The geometrical error after registration (green) with superposed
contours of the original MRI image (red). The maximum (green) intensity cor-
responds to an error of 1
.
5 pixels. (Color slide.)
optimized (
E
) and of the warping index (
), the quantity measuring the quality
of the registration. The abrupt changes in the curves are caused by the transitions
between levels of the multiresolution progression; they are small thanks to the
accuracy of the spline model.
Note that the final values of both
E
and
depend strongly on the pre-
set stopping threshold, which in turn influences the optimization time. The
threshold value is a subjective compromise between the accuracy and com-
putation time. It is perfectly possible to stop optimizing only after 7 s and
skip the finest resolution level altogether, if the precision of
=
0
.
7 pix-
els is acceptable. On the other hand, after about 4 more minutes of itera-
tion, the error
descends to less than 10
−
4
pixels. However, in the authors'
opinion, such super subpixel accuracy is almost never achievable on real im-
ages, because of the noise and the unknown characteristics of the acquisition
process.
9.4.10.2
Registration of True Medical Data
Finally, we give a representative list of medical imaging registration tasks where
the described algorithm was successfully used:
Registration of ECD
11
and Xenon inhalation SPECT images [114] in the
view of atlas creation [115].
11
ECD (Technetium Ethylene Cysteine Diethylester) is a radioactively marked intra-
venously injected agent.
