Biomedical Engineering Reference
In-Depth Information
Based on this speed function, the evolution process is governed by the following
equation:
V
(
h
)
S
(
h, γ
h
)
S
(
h, γ
h
)
−
V
(
h
)
S
(
h, γ
h
)
φ
I
n
iso
(
h, ν
+1)=
φ
I
m
iso
(
γ
h
)+
φ
I
n
iso
(
h, ν
)
,
(11)
where
h
=1
,...,
denotes the iso-surface points on image
I
t
(
·
), and
γ
h
is its
corresponding iso-surface point on
I
s
(
·
). We have tested our proposed deformable
registration technique on various 2D and 3D medical images (e.g., kidney, lung,
brain). In this work, we present some results corresponding to the application of
our registration technique on two T1-weighted brain MRIs of the same patient
acquired at different times (
H
1 year apart). Each of the two datasets is of size
256
×
200, with a voxel size of 1
×
1
×
1 mm
3
.
The performance of our approach was assessed qualitatively and compared
to our own implementation of the free form deformation technique [75]. For
a quantitative assessment of our method's accuracy, we proposed a validation
framework using finite-elements methods (see [69] for more details). For a visual
assessment of the quality of our approach, we fused the two registered volumes in
a checkerboard visualization, as shown in Figure 11. One can clearly see that the
connectivity between the two volumes is smoother both at the edges and inside the
brain region.
≈
4.
PROPOSED CLASSIFICATION APPROACHES
The main objective of the present work is to devise new techniques that allow
the classification of autistic subjects vs. typically developing ones by analyzing
their respective brain MR images. To this end, we aim at taking advantage of
the abnormalities of some brain regions, in autistic patients relative to controls, as
reported in the neuropathological and neuroimaging literature. We will focus on
analyzing the white matter (WM) and the corpus callosum (CC) using the image-
processing tools presented in previous sections. For the WM analysis, both the
postmortem and savant datasets will be used, while, due to geometric distortions
in the postmortem data, only the savant MRI scans will be used to investigate the
discriminatory measures that the CCs may reveal. To overcome the limitations
of the traditional techniques, which mainly depend on volumetric descriptions of
different brain structures, and hence are sensitive to the segmentation results as well
as to selection of the confounding parameters such as age and sex, our approaches
are based on shape descriptions and geometrical models. In the following sections
we present a description of our approaches followed by the corresponding results
and discussions.
