Data interoperability of DTI-TK for DTI analysis&
A preview of ITK-SNAP 2.0
Gary Hui Zhang, Paul A Yushkevich, and James C Gee
Penn Image Computing & Science Laboratory (PICSL)Department of Radiology, University of Pennsylvania
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of DTI-TK for DTI analysis
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
e1
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
e1
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for a single subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A typical DTI analysis pipeline for group studies
subject 1
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
subject 2
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
subject n
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Population studies Spatial Normalization
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
How do existing DTI tools support DTI analysis?
each subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Spatial Normalization
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
How do existing DTI tools support DTI analysis?
each subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Spatial Normalization
CaminoLargest collection of tensor reconstruction algorithms & HARDI
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
How do existing DTI tools support DTI analysis?
each subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Spatial Normalization
CaminoLargest collection of tensor reconstruction algorithms & HARDI
FSLProbabilistic tractography &Tract-based spatial statistics (TBSS)
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
How do existing DTI tools support DTI analysis?
each subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Spatial Normalization
CaminoLargest collection of tensor reconstruction algorithms & HARDI
FSLProbabilistic tractography &Tract-based spatial statistics (TBSS)
DTIStudioInteractive deterministic tractography &Tract-specific ROI analysis
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
How do existing DTI tools support DTI analysis?
each subject
Tensor reconstruction
Diffusion-Weighed Images
Diffusion-Tensor Images
Fiber Tractography
White Matter (WM) Tracts
Feature Computation
Measures of WM Tracts
Spatial Normalization
CaminoLargest collection of tensor reconstruction algorithms & HARDI
FSLProbabilistic tractography &Tract-based spatial statistics (TBSS)
DTIStudioInteractive deterministic tractography &Tract-specific ROI analysis
DTI-TKDTI spatial normalization + atlas construction & Tract-specific analysis
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
DTI ToolKit: A Spatial Normalization and Atlas Construction Toolkit
Optimized for Examining White Matter Morphometry Using DTI Data.
Control Population
Subject 1
Subject 2
Subject 3
Subject 4
Disease Population
Subject 1
Subject 2
Subject 3
Subject 4
Atlas
Control Population
Subject 1
Subject 2
Subject 3
Subject 4
Disease Population
Subject 1
Subject 2
Subject 3
Subject 4
More discriminatingimage features
Better Registration
Closest to the average ofthe populations in shape and features
!
"
Spatial normalization and atlas construction White matter morphometry
whole-brain
tract-specific
T1 DTI
?
?
Tensor-based registration leverages rich
discriminating features afforded by DTI !
Population-specific white matter
atlas with shape-averaging"
Hui Zhang, Paul A Yushkevich, and James C Gee
Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania
Summary of Key Features:
• Open standard-based file IO support: NIfTI format for scalar, vector
and tensor image volumes
• Tool chains for manipulating tensor image volumes: resampling,
smoothing, warping, registration and visualization
• Pipelines for White Matter Morphometry: spatial normalization and
atlas construction for population-based studies
• Built-in cluster-computing support via Sun Grid Engine
• Interoperability with other popular DTI tools: AFNI, Camino, FSL
• Interoperability with ITK-SNAP to support multi-modal segmentation
Coming soon:
• Interoperability with DTI Studio
• Tract-specific analysis [4]
Binaries for Linux and Mac OS X Available at http://www.nitrc.org/projects/dtitk
References:
[1] Zhang et al. Deformable registration of diffusion tensor MR images
with explicit orientation optimization.!Medical Image Analysis, 10(5):
764-785, October 2006.
[2] Zhang et al. Unbiased white matter atlas construction using
diffusion tensor images. In!MICCAI, volume 4792 of!LNCS, pages
211-218, October 2007.
[3] Zhang et al.. High-dimensional spatial normalization of diffusion
tensor images improves the detection of white matter differences in
amyotrophic lateral sclerosis.!IEEE Transactions on Medical Imaging,
26(11):1585-1597, November 2007.
[4] Yushkevich et al. Structure-specific statistical mapping of white
matter tracts. NeuroImage, 41(2):448-461, June 2008.
Acknowledgement:
The authors gratefully acknowledge the support from NIH via
the grants P30-NS045839, R01-EB006266, R01-DA022897,
R21-NS061111, K25-AG027785, R03-EB008200, and R03-
EB009321.
Copyright © 2009 Gary Hui Zhang
For download, visit http://www.nitrc.org/projects/dtitkSunday, June 21, 2009
DTI-TK Quick Look Plugin for Mac OSXAll Downloads
All Categories
Aperture
Apple
Audio
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206K
About DTI-TK Quick Look Plugin
This plugin uses the Mac OS X
Leopard’s built-in innovative Quick
Look framework to enable a quick
assessment of any 3-dimensional
image volume in the supported
medical image formats (NIfTI /
Analyze / FreeSurfer) directly from
the Finder. Using the Finder’s Cover
Flow mode, a large collection of
medical images can be browsed
through and quickly inspected just
as easy as flipping through your
photos. Furthermore, a large
number of images can be compared
side-by-side by selecting them
together in the Finder, then pressing
the space bar to bring up the Quick
Look preview mode.
What’s New in this Version
- Improved user feedback for failed
image preview
Company: university of pennsylvania
Version: 1.7.3
Post Date: June 8, 2009
License: Freeware
File Size: 206K
URL Type: Download
Download ID: 24493
206K
System Requirements
Mac OS X 10.5 or later
Download Details
DTI-TK Quick Look Plugin 1.7.3Recently Added to
Imaging & 3D
ViewIt 2.31
06/19/2009
3D Image Commander 1.05
06/19/2009
solidThinking 7.6
06/18/2009
Contenta Converter Premium
4.5
06/18/2009
OSG Composer CAD 1.0
06/18/2009
Vue Personal Learning Edition
7.5
06/17/2009
Microspot Interiors
Professional 4.1
06/17/2009
PhotoK 0304
06/17/2009
Goodies: Keynote Objects FX
1.0
06/17/2009
Toycamera AnalogColor 0.3
06/17/2009
Apple is providing links to these applications as a courtesy, and makes no representations regarding the applications or any information related thereto. Any questions, complaints or claims regarding
the applications must be directed to the appropriate software vendor.
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
DTI-TK Quick Look Plugin: Cover Flow Mode
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
DTI-TK Quick Look Plugin: Multi-Volume Preview
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
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Dyx Dyy Dzy
Dzx Dzy Dzz
#
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Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
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Dxx Dyx Dzx
Dyx Dyy Dzy
Dzx Dzy Dzz
#
$
= !1e1eT
1 + !2e2eT
2 + !3e3eT
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matrix representation
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
!
"
Dxx Dyx Dzx
Dyx Dyy Dzy
Dzx Dzy Dzz
#
$
= !1e1eT
1 + !2e2eT
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matrix representation
eigensystem representation
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
!
"
Dxx Dyx Dzx
Dyx Dyy Dzy
Dzx Dzy Dzz
#
$
= !1e1eT
1 + !2e2eT
2 + !3e3eT
3
(Dxx, Dyx, Dyy, Dzx, Dzy, Dzz)DTI-TK This is the NIfTI Tensor standardlower triangular
matrix representation
eigensystem representation
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
!
"
Dxx Dyx Dzx
Dyx Dyy Dzy
Dzx Dzy Dzz
#
$
= !1e1eT
1 + !2e2eT
2 + !3e3eT
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(Dxx, Dyx, Dyy, Dzx, Dzy, Dzz)DTI-TK This is the NIfTI Tensor standardlower triangular
Camino Dxx, Dyy, Dzz, Dyx, Dzx, Dzy
individual NIfTI scalar files
matrix representation
eigensystem representation
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
!
"
Dxx Dyx Dzx
Dyx Dyy Dzy
Dzx Dzy Dzz
#
$
= !1e1eT
1 + !2e2eT
2 + !3e3eT
3
(Dxx, Dyx, Dyy, Dzx, Dzy, Dzz)DTI-TK This is the NIfTI Tensor standardlower triangular
Camino Dxx, Dyy, Dzz, Dyx, Dzx, Dzy
individual NIfTI scalar files
(Dxx, Dyx, Dzx, Dyy, Dzy, Dzz)FSL !1,!2,!3, e1, e2, e3 or upper triangularindividual NIfTI scalar or vector files
matrix representation
eigensystem representation
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability of diffusion tensor images
D =
!
"
Dxx Dyx Dzx
Dyx Dyy Dzy
Dzx Dzy Dzz
#
$
= !1e1eT
1 + !2e2eT
2 + !3e3eT
3
(Dxx, Dyx, Dyy, Dzx, Dzy, Dzz)DTI-TK This is the NIfTI Tensor standardlower triangular
Camino Dxx, Dyy, Dzz, Dyx, Dzx, Dzy
individual NIfTI scalar files
(Dxx, Dyx, Dzx, Dyy, Dzy, Dzz)FSL !1,!2,!3, e1, e2, e3 or upper triangularindividual NIfTI scalar or vector files
matrix representation
eigensystem representation
DTIStudio Dxx, Dyy, Dzz, Dyx, Dzx, Dzy
individual Analyze files for export
FA, e1
individual raw binary files for import
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
• Users can choose their favorite tools for tensor reconstruction
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
• Users can choose their favorite tools for tensor reconstruction
• Minimal adoption barrier for users with existing DTI analysis pipeline
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
• Users can choose their favorite tools for tensor reconstruction
• Minimal adoption barrier for users with existing DTI analysis pipeline
• Access to new capability of DTI-TK, such as the tract-specific analysis.
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
• Users can choose their favorite tools for tensor reconstruction
• Minimal adoption barrier for users with existing DTI analysis pipeline
• Access to new capability of DTI-TK, such as the tract-specific analysis.
• Improve the quality of DTI analysis within the neuroimaging community
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
• Users can choose their favorite tools for tensor reconstruction
• Minimal adoption barrier for users with existing DTI analysis pipeline
• Access to new capability of DTI-TK, such as the tract-specific analysis.
• Improve the quality of DTI analysis within the neuroimaging community
• Users can now choose the best available tool for each component in their analysis pipeline
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Data interoperability tools in DTI-TK
• Interoperability to Camino, FSL, and DTIStudio
• fully implemented, tested, and documented
• Benefits
• Make the core capability of DTI-TK accessible to users of major DTI tools
• Users can choose their favorite tools for tensor reconstruction
• Minimal adoption barrier for users with existing DTI analysis pipeline
• Access to new capability of DTI-TK, such as the tract-specific analysis.
• Improve the quality of DTI analysis within the neuroimaging community
• Users can now choose the best available tool for each component in their analysis pipeline
• New techniques can be more easily compared to existing tools
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
A preview of ITK-SNAP 2.0
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
• Key enhancements implemented for version 2.0
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
• Key enhancements implemented for version 2.0
• Full featured multi-session synchronized image navigation - enabling synchronized cursor, zoom and pan
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
• Key enhancements implemented for version 2.0
• Full featured multi-session synchronized image navigation - enabling synchronized cursor, zoom and pan
• Full NIfTI support - enabling synchronized image navigation across multiple ITK-SNAP sessions even when images have oblique orientation
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
• Key enhancements implemented for version 2.0
• Full featured multi-session synchronized image navigation - enabling synchronized cursor, zoom and pan
• Full NIfTI support - enabling synchronized image navigation across multiple ITK-SNAP sessions even when images have oblique orientation
• Full featured multiple image overlay support - enabling multiple RGB or greyscale image overlay as well as greyscale to color mapping
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
• Key enhancements implemented for version 2.0
• Full featured multi-session synchronized image navigation - enabling synchronized cursor, zoom and pan
• Full NIfTI support - enabling synchronized image navigation across multiple ITK-SNAP sessions even when images have oblique orientation
• Full featured multiple image overlay support - enabling multiple RGB or greyscale image overlay as well as greyscale to color mapping
• Enhanced support for manual segmentation via the new adaptive brush
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Overview of ITK-SNAP
• ITK-SNAP is a software application used to segment structures in 3D medical images. It provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
• Key enhancements implemented for version 2.0
• Full featured multi-session synchronized image navigation - enabling synchronized cursor, zoom and pan
• Full NIfTI support - enabling synchronized image navigation across multiple ITK-SNAP sessions even when images have oblique orientation
• Full featured multiple image overlay support - enabling multiple RGB or greyscale image overlay as well as greyscale to color mapping
• Enhanced support for manual segmentation via the new adaptive brush
• User experience enhancement, including redesigned user interface, native file chooser, and automatic check for update
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
ITK-SNAP 2.0 Preview Demo
For download, visit http://www.itksnap.org
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009
Acknowledgement
• DTI-TK
• NIH grant: R03 EB009321
• DTI-TK user community
• ITK-SNAP
• NIH grant: R03 EB008200
• Prof. Guido Gerig, original SNAP developers at UNC
• ITK-SNAP user community
Thank you for your attention.
Copyright © 2009 Gary Hui Zhang
Sunday, June 21, 2009