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Fiber feature map based landmark initialization for highly deformable DTI registration.
[krabbe disease]
This
paper
presents
a
novel
pipeline
for
the
registration
of
diffusion
tensor
images
(
DTI
)
with
large
pathological
variations
to
normal
controls
based
on
the
use
of
a
novel
feature
map
derived
from
white
matter
(
WM
)
fiber
tracts
.
The
research
presented
aims
towards
an
atlas
based
DTI
analysis
of
subjects
with
considerable
brain
pathologies
such
as
tumors
or
hydrocephalus
.
In
this
paper
,
we
propose
a
novel
feature
map
that
is
robust
against
variations
in
WM
fiber
tract
integrity
and
use
these
feature
maps
to
determine
a
landmark
correspondence
using
a
3
D
point
correspondence
algorithm
.
This
correspondence
drives
a
deformation
field
computed
using
Gaussian
radial
basis
functions
(
RBF
)
.
This
field
is
employed
as
an
initialization
to
a
standard
deformable
registration
method
like
demons
.
We
present
early
preliminary
results
on
the
registration
of
a
normal
control
dataset
to
a
dataset
with
abnormally
enlarged
lateral
ventricles
affected
by
fatal
demyelinating
Krabbe
disease
.
The
results
are
analyzed
based
on
a
regional
tensor
matching
criterion
and
a
visual
assessment
of
overlap
of
major
WM
fiber
tracts
.
While
further
evaluation
and
improvements
are
necessary
,
the
results
presented
in
this
paper
highlight
the
potential
of
our
method
in
handling
registration
of
subjects
with
severe
WM
pathology
.
Diseases
Validation
Diseases presenting
"white matter"
symptom
22q11.2 deletion syndrome
adrenomyeloneuropathy
alexander disease
cadasil
canavan disease
classical phenylketonuria
cushing syndrome
gm1 gangliosidosis
hereditary cerebral hemorrhage with amyloidosis
homocystinuria without methylmalonic aciduria
kabuki syndrome
kallmann syndrome
krabbe disease
neonatal adrenoleukodystrophy
proteus syndrome
pyruvate dehydrogenase deficiency
sneddon syndrome
wiskott-aldrich syndrome
x-linked adrenoleukodystrophy
zellweger syndrome
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