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http://www.brain-map.org. A Big Thanks. Prof. Jason Bohland Quantitative Neuroscience Laboratory Boston University. Dr. Luis Ibanez Open Source Proponent, ITK Kitware Inc. Supplemental Material. Allen Mouse Brain Atlas. - PowerPoint PPT PresentationTRANSCRIPT
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http://www.brain-map.org
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A Big Thanks
Prof. Jason BohlandQuantitative Neuroscience LaboratoryBoston University
Dr. Luis IbanezOpen Source Proponent, ITKKitware Inc.
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Supplemental Material
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• Genome-wide atlas of gene expression throughout the mouse brain (N=1,2 or a few mice/gene)
• 56 day-old (young adult) C57BL/6J mice• High-throughput experiments using in situ
hybridization• Pipeline - sectioning, ISH, digital microscopy, image
analysis, atlas registration
Allen Mouse Brain Atlas
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The Process
Construction and representation of the Anatomic Gene Expression Atlas (AGEA).
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Nissl-Stained Atlas – Ground Truth
(a) Level 53 coronal plate (bregma 0.145 mm) from the The Allen Reference Atlas (ARA) delineating 2D anatomic boundaries of a Nissl-stained mouse brain section.
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Bregma – Neurological Context
http://en.wikipedia.org/wiki/Bregma
bregma located at the intersection of the coronal and sagittal sutures.
Level 53 coronal plate (bregma 0.145 mm)
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Image
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Nissl
http://en.wikipedia.org/wiki/File:NisslHippo2.jpg
Nissl-stained histological section through the rodent hippocampus showing various classes of cells (neurons and glia).
Motor nerve cell from ventral horn of medulla spinalis of rabbit. The angular ande spindle-shaped Nissl bodies are well shown• Nissl stains the cell body esp.
endoplasmic reticulum.
• Basic dyes (e.g. aniline, thionine, or cresyl violet) to stain negatively charged RNA blue,
• Nissl substance (rough endoplasmic reticulum) appears dark blue from ribosomal RNA
• DNA stains a similar color
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Atlas Assembly (b) 3D assembly of high-level ARA structures formed by 3D reconstruction of the Nissl sections. The 3D ARA space is partitioned into 200-mm^3 voxels forming the smallest spatial unit for analysis.
• New annotated anatomical reference atlas (Hong-Wei Dong, 2007) • 528 coronal Nissl sections: unfixed, frozen mouse brain (25μm thick)• 132 sections, with 100μm spacing, annotated over1000 brain• All image data are mapped to common coordinate space • Waxholm - http://en.wikipedia.org/wiki/Waxholm_space
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Creating Geometry from Images
Placenta
H+E Slides Alignment
SegmentationVisualization/Surface Extraction
Aperio
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Digital Placenta
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Virtual Cellular ReconstructionsBefore using cellular segmentation Using cellular segmentations
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Plane-by-Plane Reconstruction
Mammary duct segmentation Visualization: N-point function feature space
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What We Did …
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Sub-Sampling by Half
Origin (Ox,Oy)
New Origin(O’x,O’y)
New SpacingS’y
New SpacingS’x
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Resampling in ITK
Transform
Interpolator
Origin
Spacing
Region Start
Region Size
Resample Filter
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Image Registration
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Formulation
• Assume correspondences are known
• Find such f() and g() such that the images are best matched
I2(x,y)=g(I1(f(x,y))
f() – spatial transformationg() – intensity transformation
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24
General FormulationThe general formulation for registration with regularization is:
where is the Error term
is the regularization parameter
is the penalty term
22|||| bAx
22|||| Lx
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Registration
FixedImage
MovingImage
Metric
Transform
Interpolator
Optimizer
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Image Metrics• Mean Squares• Normalized Correlation• Mean Reciprocal Square
Difference• Mutual Information
- Viola-Wells- Mattes- Histogram based- Histogram normalized
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Plotting the MetricMean Squared Differences
Transform Parametric Space
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Plotting the MetricMean Squared Differences
Transform Parametric Space
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Plotting the MetricMean Squared Differences – A
PROBLEM
Transform Parametric Space
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Registration
FixedImage
MovingImage
Metric
Transform
Interpolator
Optimizer
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Transforms• Translation• Scaling• Rotation• Rigid3D• Rigid2D• Affine• BSplines• Splines: TPS, EBS, VS
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Rigid Transformation• Rotation(R)• Translation(t)• Similarity(scale)
2
22 y
xp
1
11 y
xp
12 pRstp
)cos()sin()sin()cos(
R
2
11 s
ss
2
11 t
tt
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Registration
FixedImage
MovingImage
Metric
Transform
Interpolator
Optimizer
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Interpolators
• Nearest Neighbor• Linear• BSpline
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Optimizers• Gradient Descent• Regular Step Gradient Descent• Conjugate Gradient• Levenberg-Marquardt• One plus One Evolutionary
Algorithm
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Gradient Descent Optimizerf( x , y )
S = L G( x , y )∙f( x , y )∆G( x , y ) =
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Gradient Descent Optimizerf( x , y )
S = L ∙ G( x , y )f( x , y )∆G( x , y ) =
L too large
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Gradient Descent Optimizerf( x , y )
S = L ∙ G( x , y )f( x , y )∆G( x , y ) =
L too small
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Registration in ITK
ImageRegistrationFramework
MultiResolution
RegistrationFramework
PDEBased
Registration
FEMBased
Registration
Components
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Construction of ARA and ISH
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Allen Reference Atlas
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Allen Reference Atlas
• 3D Nissl volume comes from rigid reconstruction
• Each section reoriented to match adjacent images as closely as possible
• A 1.5T low resolution 3D average MRI volume used to ensure reconstruction is realistic
• Reoriented Nissl section down-sampled, converted to grayscale
• Isotropic 25μm grayscale volume.
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Anatomy
• 208 large structures and structural groupings extracted
• Projected & smoothed onto 3D atlas volume to for structural annotation
• Additional decomposition of cortex into an intersection of 202 regions and areas