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Transcript of Http://. A Big Thanks Prof. Jason Bohland Quantitative Neuroscience Laboratory Boston University Dr....
http://www.brain-map.org
A Big Thanks
Prof. Jason BohlandQuantitative Neuroscience LaboratoryBoston University
Dr. Luis IbanezOpen Source Proponent, ITKKitware Inc.
Supplemental Material
• 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
The Process
Construction and representation of the Anatomic Gene Expression Atlas (AGEA).
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.
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)
Image
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
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
Creating Geometry from Images
Placenta
H+E Slides Alignment
SegmentationVisualization/Surface Extraction
Aperio
Digital Placenta
Virtual Cellular ReconstructionsBefore using cellular segmentation Using cellular segmentations
Plane-by-Plane Reconstruction
Mammary duct segmentation Visualization: N-point function feature space
What We Did …
Sub-Sampling by Half
Origin (Ox,Oy)
New Origin
(O’x,O’y)
New Spacing
S’y
New Spacing
S’x
Resampling in ITK
Transform
Interpolator
Origin
Spacing
Region Start
Region Size
Resample Filter
Image Registration
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
24
General Formulation
The general formulation for registration with regularization is:
where is the Error term
is the regularization parameter
is the penalty term
22|||| bAx
22|||| Lx
Registration
FixedImage
MovingImage
Metric
Transform
Interpolator
Optimizer
Image Metrics
• Mean Squares• Normalized Correlation• Mean Reciprocal Square
Difference• Mutual Information
- Viola-Wells- Mattes- Histogram based- Histogram normalized
Plotting the MetricMean Squared Differences
Transform Parametric Space
Plotting the MetricMean Squared Differences
Transform Parametric Space
Plotting the MetricMean Squared Differences – A
PROBLEM
Transform Parametric Space
Registration
FixedImage
MovingImage
Metric
Transform
Interpolator
Optimizer
Transforms
• Translation• Scaling• Rotation• Rigid3D• Rigid2D• Affine• BSplines• Splines: TPS, EBS, VS
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
Registration
FixedImage
MovingImage
Metric
Transform
Interpolator
Optimizer
Interpolators
• Nearest Neighbor• Linear• BSpline
Optimizers
• Gradient Descent• Regular Step Gradient Descent• Conjugate Gradient• Levenberg-Marquardt• One plus One Evolutionary
Algorithm
Gradient Descent Optimizerf( x , y )
S = L G( x , y )∙f( x , y )∆G( x , y ) =
Gradient Descent Optimizerf( x , y )
S = L ∙ G( x , y )f( x , y )∆G( x , y ) =
L too large
Gradient Descent Optimizerf( x , y )
S = L ∙ G( x , y )f( x , y )∆G( x , y ) =
L too small
Registration in ITK
ImageRegistrationFramework
MultiResolution
RegistrationFramework
PDEBased
Registration
FEMBased
Registration
Components
Construction of ARA and ISH
Allen Reference Atlas
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.
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