motivation Mads Nielsen 2 Registration in Medical Imaging Find correspondences intrapatient inhale phase to exhale phase Castillo R Castillo E Guerra R Johnson VE McPhail T Garg AK Guerrero T 2009 ID: 535351
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Slide1
Registration motivation
Mads NielsenSlide2
2
Registration in Medical Imaging
Find correspondences – intrapatient:
inhale phase to exhale phase
Castillo, R., Castillo, E., Guerra, R., Johnson, V.E., McPhail, T., Garg, A.K., Guerrero, T. 2009
“A framework for
evaluation of deformable image registration spatial accuracy using large landmark point sets”
Phys Med Biol 54 1849-1870.
1
1Slide3
Monitoring subtle changes
Local is better!
Problem: which pixel goes where?
Baseline
Follow-upSlide4
Optimization
Transform
Fixed
Image
Moving
Image
Cost
Function
Transform Coefficients
Incorporate model of density change
Image registrationSlide5
Disease monitoring usingimage registration
Possible to indicate which locations change
Consistent in time
Local changes predict decline betterSlide6
6
Registration in Medical Imaging
Find correspondences – intrapatient:
Marcus, DS, Fotenos, AF, Csernansky, JG, Morris, JC, Buckner, RL, 2009. Open Access Series of Imaging Studies
(OASIS): Longitudinal MRI Data in Nondemented and Demented Older Adults. Journal of Cognitive Neuroscience, in press.
disease progression
2
2Slide7
Readings: Atrophy Assessment
7Slide8
Readings: Atrophy Accuracy Test
8
Group
Hippocampus baseline volume
FreeSurfer (mm3)
Cross-Sectional FreeSurfer (%)
Longitudinal FreeSurfer (%)
Hippocampus baseline volumeSynarc (mm3)
Cross-Sectional Synarc (%)Registration Based(%)Normal (N = 27)3410 ± 329 (L)3430 ± 416 (R)-0.9 ± 2.60.9 ± 6.6-0.8 ± 1.4 -0.6 ± 2.42333 ± 330 (L)2268 ± 299 (R)-1.9 ± 2.0-1.4 ± 2.9
-0.8 ± 2.0-0.6 ± 1.9MCI (N = 37)2992 ± 281(L)3070 ± 420(R)-0.9 ± 2.9-0.5 ± 7.0-1.2 ± 1.5-1.4 ± 3.02081 ± 312 (L)2075 ± 363 (R)-2.5 ± 3.1-3.1 ± 3.3-1.1 ± 1.2-2.0 ± 2.0AD (N = 57) 2542 ± 349(L)2728 ± 621(R)-4.3 ± 3.1-4.0 ± 7.1
-4.2 ± 2.4-4.4 ± 4.11787 ± 482 (L)1773 ± 484 (R)
-4.0 ± 4.4
-5.2 ± 4.3
-4.2 ± 1.6
-4.4 ±
2.4
101
Subjects From ADNI. Changes from BL
M12Slide9
9
Registration at Large
and
Small Scale
Inter-patient variation at
large scaleAtrophy at smaller scale
Data from: Marcus, DS,
Fotenos, AF, Csernansky, JG,
Morris, JC, Buckner, RL, 2009. Open Access Series of Imaging Studies (OASIS): “Longitudinal MRI Data in Nondemented and Demented Older Adults.“Journal of Cognitive Neuroscience, in press.
disease progression2Slide10
10
LDDMM/LDDKBM registration
Large Deformation
Diffeomorphic
Metric MappingDomain , deformations Find minimizing
regularization/smoothness term
matching term ImagesSlide11
in LDDMM, regularization is the
length of minimal
paths
If Sobolev-norm <Lv,v>
on v, then diffeomorphism
L is the momentum
Operator: Lv = aV
t = ∫K(:,x)at(x)dx
11Manifold/Lie Group Formulation