Diffusion Tensor Imaging: from Dicom to Nrrd

Surgical Planning Laboratoryhttp://www.slicer.org-1-

Brigham and Women’s Hospital

Diffusion Tensor Imaging: from Dicom to Nrrd

Sonia Pujol, Ph.D.Randy Gollub, M.D., Ph.D.

National Alliance for Medical Image Computing



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 Dr. Gordon Kindlmann

Dartmouth Hitchcock Medical Center Thanks to Dr. Andy Saykin



Raw Data

Goal of the Tutorial

Training on how to convert DICOM DWI data to the Nrrd File format, compatible with Slicer visualization and analysis

Raw DataRaw Data

Nrrd

Header

Dicom HeaderDicom

HeaderDicom HeaderDicom

Header

Raw Data



Overview

• Part 1: DWI data specificity

• Part 2: Nrrd description

• Part 3: Generating Nrrd Files

• Part 4: Working with DICOM DWI training data

• Part 5: Orientation validation within Slicer



Diffusion Weighted Imaging

The signal is dimmer when the direction of the applied gradient is parallel to the principal direction of diffusion.

Diffusion Sensitizing Gradients

Diffusion Weighted Images



Diffusion Weighted Imaging (DWI)

Example: Correlation between the orientation of the 11th gradient and the signal intensity in the Splenium of the Corpus Callosum



Diffusion Weighted Imaging

(Stejskal and Tanner 1965, Basser 1994 )

{Si} represent the signal intensities in presence of the diffusion sensitizing gradients gi

b is the diffusion weighted parameter

Si S0 e b ˆ g iT D ˆ g i




Background• Challenge: Concise and standardized description of

the information contained in DWI data. • Current situation:

– DICOM (Supplement 49) contains information on how to represent b-value and gradient directions of DWI

– However every MR Scanner manufacturer has their own unique way of archiving the relevant image acquisition parameters

– The definition of the coordinate frame of the diffusion gradients is not explicitly recorded in the header

• Proposed Solution: Nrrd format



Which image is correct ?



The left one is correct



Overview








Nearly Raw Raster Data (Nrrd)• The flexible Nrrd format includes a single header file

and image file(s) that can be separate or combined.

• A Nrrd header accurately represents N-dimensional raster information for scientific visualization and medical image processing.

Raw DataRaw Data

Raw DataNrrd

Header+



Nrrd file format

• NA-MIC has developed a robust way of using the Nrrd format to represent DWI volumes



Nrrd file format• DWI data written into Nrrd format with appropriate

parameters can be read into 3D Slicer



Coordinate Frames



(X,Y,Z) (I,J,K)

Courtesy G.Kindlmann




Coordinate Frames

DWI Image Orientation

(I,J,K)


(X,Y,Z) (X,Y,Z) (I,J,K)

Patient Space




Transformation matrices

T: IJKRAS

(X,Y,Z) (I,J,K)

T: XYZRAS

(R,A,S) Courtesy G.Kindlmann



Nrrd Terminology

T: XYZRAS

(X,Y,Z) (I,J,K)

(R,A,S)

T: IJKRAS




Nrrd requirements for DWI data

To generate a Nrrd header for DWI data, you’ll

need to know information about data representation:

• DWI Volume characteristics– Data Type – Endianess– Dimensions

• Disk Storage– Axis Ordering



Nrrd requirements for DWI data

To generate a Nrrd header for DWI data, you’ll

need to know the acquisition parameters:

• Coordinate Frames– DWI Image Orientation– Gradient Measurement Frame



Overview








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 a Nrrd reader to load DWI volumes in Nrrd

format



Unu syntax

• General Syntax:

unu cmd -i input -o output

• Tips:

“unu” list of unu commands

“unu cmd” help on cmd



Unu syntax: ‘make’ command

• ‘make’ syntax:

unu make -i input -o output

• ‘make’ documentation:

unu make help on make



Running unu on Windows

To run the unu command from the Tk

console, type unu.

On Windows, you do not need to be in the

directory win32/bin/teem-build/bin

the unu commands run from any location.



Running unu on Mac/Linux/Solaris

To run the unu command from the Tk console,

you need to enter the whole path to the /bin

directory

Ex: Mac ../slicer2.6-opt-darwin-ppc-2006-05-18/Lib/darwin-ppc/teem-build/bin



Overview








DICOM DWI Training Data

• 2 Baselines and 12 Gradients

• 504 DICOM images named S4.xxx where xxx is the image number



DWI Training Data

Type the command cd and enter the path to your data in the Tk Console. Type ls to list all the data files.



DWI Training Data

The dataset is composed of 504 images named S4.xxx



unu make -h --input S4.%03d 1 504 1 2 --encoding raw --byteskip -1

Unu command (Windows)Type the unu command with the input, encoding and byteskip fields

Min index

Max index Increment

2D Image Read backwards from end of file

Do not hit Enter




Unu command (Mac/Linux)Type the unu command with the input, encoding and byteskip fields

Min index

Max index Increment

2D Image Read backwards from end of file

slicer2.6-opt-darwin-ppc-2006-05-18/Lib/darwin-

ppc/teem-build/bin



Numbers as file naming convention (*)

• % is a special character to be replaced by the specific file number (cf C/C++ printf command)

• %03d means a 3 digit number with zero “padding”: Padding means there will be zeros instead of spaces at the beginning of the number

Ex: %03d S4.001 for file number 1%03d S4.024 for file number 24

• This is a compact way to refer to the whole image sequence

(*) Background information




Read the DICOM Header

Click on AddVolume



Select the Properties Dicom

The Props panel appears.




Click on Select DicomVolume and browse to

load the dataset located in

the directory dwi-dicom

The Dicom Props panel appears.




Slicer displays the list of

Dicom files in the directory.

Click on OK

Read the Dicom Header



Click on Extract Header to display the content of the Dicom Header.




Slicer displays the content of the Dicom Header.

This information will be used to generate the Nrrd header.




Extract the values corresponding to the following information:

- Data Type

- Endianess

- Image Dimensions

Extracting the volume characteristics



- Data Type: Short

- Endianess: Little




Unu CommandAdd the fields endian and type to the unu command

--endian little --type short



The dataset was acquired with Nb=2 Baselines and Ng=12 Gradients


Image Dimensions: 256 pixels x 256 pixels



DICOM DWI Training Data

• 2 Baselines and 12 Gradients

• 504 DICOM images named S4.xxx where xxx is the image number



The dataset was acquired with Nb=2 Baselines and Ng=12 Gradients

n=NbxNg = 12 + 2 = 14 intensity values/voxel

NSlices= NdicomImages/n = 504/14 = 36 slices


Image Dimensions: 256 pixels x 256 pixels



Unu Command

--size 256 256 36 14

--centering cell cell cell none

Medical images are

cell-centered samples

Add the fields size and centering to the unu command



Slice Thickness

Extract the slice thickness from the Dicom header



Slice Thickness

slice thickness = 3.00 mm



Slice Thickness

--thickness nan nan 3.0 nan

Add the field thickness to the unu command



Building the transformation matricesWe specifically change orientation from the DICOM default of LeftPosterior-Superior (LPS) to Right-Anterior-Superior (RAS)so that the data can be viewed in Slicer coordinate space

DICOM: LPS SLICER: RAS



Space DirectionsAdd the field space to the unu command

--space right-anterior-superior



Space Directions

Extract the pixel size from the Dicom Header.



Space Directions

Pixel size = 0.9375 mm x 0.9375 mm

The dataset was acquired with Superior-Inferior slice ordering



Space Directions

--directions “(-0.9375,0,0) (0,-0.9375,0) (0,0,-3) none“

Add the fields directions and unit to the unu command




Space Origin


The space origin is the position of the first pixel in the first image.

This information is contained in the Dicom Header of the first slice.



Space Origin

The space origin information is located in the Dicom header

[0020,0032, Image Position Patient ]




Space Origin

Click on Cancel to come back to the Main menu

Create a directory calledFirstSlice and copy the first fileS4.001 of the Dicom-dwidataset



Space Origin

Click Add Volumeselect the tab Props, and the format DICOM



Space Origin

Click on Select DICOM Volume

Select the directory /FirstSlicecontaining the first slice



Space Origin

Click on List Headers to

display the content of the

header of the first image.



Space Origin

Slicer displays the content of

the header of the first image.



Space Origin

Scroll down to display the value of the tag [0020,0032, Image Position Patient ]



Space Origin

[0020,0032, Image Position Patient ] = -125.0, -124.09, 79.30



Space Origin

Click on OK to close the Dicom Header Window



Space Origin

--origin "(+125.0,+124.10,79.30)"

Add the field origin to the unu command




Measurement Frame



Measurement Frame

--measurementframe “(0,-1,0) (1,0,0) (0,0,-1)"

Add the field measurement frame to the unu command



Axis Ordering




Axis Ordering

--kind space space space list

Add the field kinds to the unu command

Axis Ordering: columns, rows, slices, intensity values



Output FileAdd the field output to the unu command

--output myNrrdDWI.nhdr



Output File

Type ls in the Tk Console

The file myNrrdDWI.nhdr is listed in the directory



Acquisition parametersOpen the file MyNrrdDWI.nhdr with a text Editor



Acquisition parametersOpen a web browser at the location

http://www.na-mic.org/Wiki/index.php/Dartmouth-DWI-parameters



Acquisition parametersCopy the acquisition parameters from this wiki page to the end of the file

MyNrrdDWI.nhdr, hit Enter and save the resulting file



Result

Final result of the tutorial: Nrrd header for the DWI training dataset



Overview








Loading the Nrrd Volume

Click on Cancel to come back to the Main Menu




Click on Add Volume to load the DWI training dataset using the Nrrd header




Select Nrrd Reader in the Properties field

The Props Panel of the module Volumes appears.




Click on Apply

Check that the path to the file myNrrdDWI.nhdr is correct. If needed, manually enter it

Browse to load the file myNrrdDWI.nhdr




Slicer loads the Nrrd DWI dataset

Left-click on Or and change the orientation to Slices




Change the FOV to 2000




The sagittal and coronal viewers display the 14 DWI volumes: 2 baselines and 12 gradients




Display the axial and sagittal slices inside the viewer.

Use the axial slider to observe the baselines and gradient volumes.



Converting the DWI data to tensors

Select the module DTMRI and click on the tab Conv

Select the Input volume myNrrdDWI.nhdr and click on ConvertVolume



Converting the DWI data to tensors

Slicer displays the anatomical views of the Average Gradient volume.



Glyphs

Select the panel Glyphs in the DTMRI module

Select the Active DTMRI volume myNrrdDWI-nhdr_Tensor

Select Glyphs on Slice for the axial (red) view

Set Display Glyphs On



Glyphs

Orientation of the glyphs in the Corpus Callosum



Conclusion

• Standardized description of the information contained in DWI data.

• Rapid, intuitive visual assessment of orientation results within Slicer

• Open-Source: http://teem.sourceforge.net/nrrd/

Diffusion Tensor Imaging: from Dicom to Nrrd

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