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Converting DTI data into Nrrd file format
Sonia Pujol, Ph.D.Gordon Kindlmann, Ph.D.Randy Gollub, M.D, Ph.D.
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Acknowledgments
National Alliance for Medical Image Computing NIH U54EB005149
Neuroimage Analysis Center NIH P41RR013218
Laboratory of Mathematics in Imaging, Brigham and Women’s Hospital Thanks to Gordon Kindlmann
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Goal of the Tutorial
Training on how to generate NRRD headers DTI data and validate the orientation information within Slicer.
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Which image is correct ?
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The right one is correct
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Overview
• Part 1: NRRD description• Part 2: NRRD requirements • Part 3: Generating NRRD Files• Part 4: NRRD training data• Part 5: Orientation validation within Slicer
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Background• Challenge: Concise and standardized description of
the information contained in DWI and DTI data.• Current situation:
– DICOM (Supplement 49) contains information on how to represent b-values and gradient directions of DWI
– However no-one uses it: every vendor has their own unique way of archiving the relevant image acquisition parameters
– The definition of the coordinate frame of the diffusion gradients (or the resulting estimated tensor) is not explicitly recorded in the header.
– DICOM has no standard for tensors• Proposed Solution: Nrrd format
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Nearly Raw Raster Data
• Image files that include a NRRD header to accurately represent N-dimensional raster data for scientific visualization and medical image processing.
• NA-MIC has developed a way of using the NRRD format to represent Diffusion Weighted Images (DWI) volumes and Diffusion Tensor Images (DTI)
• NRRD DWI and NRRD DTI data can be read into 3D Slicer: the software provides you a visual tool to confirm that the orientation of the tensors is consistent with expected neuroanatomy
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DTI Pipeline
DWI imagesDiffusion Sensitizing Gradients
Dxx Dxy Dxz
Dyy Dyz
Dzz
DTI images
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Coordinate frames
DWI and DTI Image Orientation
(I,J,K)
Diffusion Sensitizing Gradients
(X,Y,Z) (X,Y,Z) (I,J,K)
Patient Space
(R,A,S)
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Transformation matrices
(X,Y,Z) (I,J,K)
(R,A,S)
T: XYZRAS
T: IJKRAS
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NRRD Terminology
(X,Y,Z) (I,J,K)
(R,A,S)
T: XYZRAS T: IJKRAS
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Overview
• Part 1: NRRD description• Part 2: NRRD requirements • Part 3: Generating NRRD Files• Part 4: NRRD training data• Part 5: Orientation validation within Slicer
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DTI RequirementsTo generate a NRRD header for DTI data, you’ll need to
know about the data representation and acquisition:DTI Volume characteristics• Data Type • Endianess• Dimensions Disk Storage• Axis OrderingCoordinate Frames• DTI Image Orientation• Gradient Measurement FrameTensor coefficients• Order of the tensor coefficients
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Overview
• Part 1: NRRD description• Part 2: NRRD requirements • Part 3: Generating NRRD Files• Part 4: NRRD training data• Part 5: Orientation validation within Slicer
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Generating NRRD Files• Nrrd files can be generated from the Tk console of Slicer using
the “unu” command line tool • unu is part of set of libraries called “Teem” compiled into Slicer
2.6(http://teem.sourceforge.net/)
• Slicer includes NRRD reader to load DTI volumes in Nrrd format
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Unu syntax• General Syntax:unu cmd -i input -o output
• Tips:“unu” list of unu commands“unu cmd” help on cmd
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Unu syntax: ‘make’ command
• ‘make’ syntax:unu make -i input -o output
• ‘make’ documentation:unu make help on make
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Overview
• Part 1: NRRD description• Part 2: NRRD requirements • Part 3: Generating NRRD Files• Part 4: NRRD training data• Part 5: Orientation validation within Slicer
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Creating NRRD header for the DTI Training Data
From the Analyze header, extract the:
• DTI Volume characteristicsData Type: Float “--type float”Endianess: Big Endian “--endian big”Dimensions: 91 109 91 6 “--size 91 109 91 6”
• Disk StorageAxis Ordering: columns, rows, slices, tensor elements “--kinds space space space 3d-symmetric-matrix”
• Tensor coefficientsOrder of the tensor coefficients: Dxx, Dyy, Dzz, Dxy,Dxz, Dyz
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DTI Training Data• Coordinate FramesDTI Image Orientation: Right-Anterior-Superior “--space ras”
• Tensors Measurement FrameT: XYZRAS “--measurement frame (1,0,0) (0,1,0) (0,0,1)”
• Space Direction and SpaceOrigin
T: IJKRAS --directions "(-1.98901,0.0,0.0) (0.0,1.99083,0.0)
(0.0,0.0,2.0) --origin "(0,0,0)"
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Complete unu Command
unu make -h -i Tensors.img --size 91 109 91 6 --type float --encoding raw --endian big --space ras --spaceunit mm mm mm --measurementframe "(1,0,0)(0,1,0)(0,0,1)“ --directions "(-1.98901,0.0,0.0) (0.0,1.99083,0.0) (0.0,0.0,2.0) none" --origin "(0,0,0)" | unu shuffle -a 3 -p 0 3 4 1 5 2 -o myTensors.nhdr
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Reordering the Tensor Coefficients
Initial tutorial dataset 0:Dxx 1:Dyy 2:Dzz 3:Dxy 4:Dxz 5:Dyz
Final tutorial dataset 0:Dxx 3:Dxy 4:Dxz 1:Dyy 5:Dyz 2:Dzz
unu shuffle –a 3 –p 0 3 4 1 5 2
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Step1: Unu Command into Slicer
Type the unu command directly in the Tk console of Slicer
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Step 2: Adding axis descriptionYou need to add an additionnal kinds field to the generated NRRD header to specify how the data is stored to disk
(This is analogous to the “Intent” field in NIfTI file format)
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Step 2: Adding axis descriptionType the following Tcl commands:
set file [open myTensors.nhdr a]
puts $file “kinds: space space space 3d-symmetric-matrix”
close $file
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Step 2: Axis description
In this example kinds states that the data is stored with the tensors coefficients in the slowest axis.
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Step 3: Viewing the NRRD HeaderType more MyNrrdFile.nhdr in the Tk console to display the content of the NRRD header you just made
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Step 3: Viewing the Nrrd Header
Slicer displays the content of the Nrrd header
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Overview
• Part 1: NRRD description• Part 2: NRRD requirements • Part 3: Generating NRRD Files• Part 4: NRRD training data• Part 5: Orientation validation within Slicer
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Loading a NRRD Volume
Click on Add Volume in the Main Panel of Slicer
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Loading a NRRD Volume
Select Nrrd Reader in the Properties field
Click on Browse and load the file myTensors.nhdr
Click on Apply
The Props Panel of the module Volumes appears.
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Loading a NRRD Volume
Slicer loads the Nrrd Tensor
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Fractional Anisotropy
Compute the Fractional Anisotropy from the Nrrd Tensor Volume using the DT-MRI module (Slicer Training 4)
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Corpus Callosum Tracts
Seed tracts in the Corpus Callosum using the tractography tools from the DT-MRI module (Slicer Training 4)
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Corpus Callosum Tracts
The orientation of the tracts within the Corpus Callosum confirms that the orientation information contained in the Nrrd file is correct.
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The right one is correct
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Conclusion
• Standardized description of the information contained in DWI and DTI data.
• Rapid, intuitive visual assessment of orientation results within Slicer
• Open-Source: http://teem.sourceforge.net/nrrd/