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