The document discusses converting DICOM diffusion weighted imaging (DWI) data to the Nrrd file format for use in 3D Slicer. It provides an overview of DWI and the Nrrd format, and describes the steps to generate a Nrrd header from the DICOM data including extracting parameters from the DICOM header like image dimensions, data type, and diffusion gradient information and coordinate frames.

1. Diffusion Tensor Imaging: from Dicom to Nrrd Sonia Pujol, Ph.D. Randy Gollub, M.D., Ph.D. National Alliance for Medical Image Computing

3. Goal of the Tutorial Training on how to convert DICOM DWI data to the Nrrd File format, compatible with Slicer visualization and analysis Raw Data Raw Data Raw Data Nrrd Header Dicom Header Dicom Header Dicom Header Dicom Header Raw Data

5. 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

6. Diffusion Weighted Imaging (DWI) Example: Correlation between the orientation of the 11 th gradient and the signal intensity in the Splenium of the Corpus Callosum

7. 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 Diffusion Weighted Images

9. Which image is correct ?

10. Which image is correct ?

11. The left one is correct

16. Coordinate Frames Diffusion Weighted Images Diffusion Sensitizing Gradients Courtesy G.Kindlmann Courtesy G.Kindlmann (X,Y,Z) (I,J,K)

17. Coordinate Frames DWI Image Orientation (I,J,K) Diffusion Sensitizing Gradients (X,Y,Z) Patient Space Courtesy G.Kindlmann (X,Y,Z) (I,J,K)

30. 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.

31. DWI Training Data The dataset is composed of 504 images named S4.xxx

32. Unu command (Windows) unu make -h --input S4.%03d 1 504 1 2 --encoding raw --byteskip -1 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

33. Unu command (Mac/Linux) unu make -h --input S4.%03d 1 504 1 2 --encoding raw --byteskip -1 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

35. Read the DICOM Header Click on AddVolume

36. Read the DICOM Header Select the Properties Dicom The Props panel appears.

37. Read the DICOM Header Click on Select Dicom Volume and browse to load the dataset located in the directory dwi-dicom The Dicom Props panel appears.

38. Read the Dicom Header Slicer displays the list of Dicom files in the directory. Click on OK

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

40. Read the Dicom Header Slicer displays the content of the Dicom Header . This information will be used to generate the Nrrd header .

42. Extracting the volume characteristics - Data Type: Short - Endianess: Little

43. Unu Command Add the fields endian and type to the unu command --endian little --type short

44. Extracting the volume characteristics The dataset was acquired with Nb=2 Baselines and Ng=12 Gradients Image Dimensions: 256 pixels x 256 pixels

47. 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

48. Slice Thickness Extract the slice thickness from the Dicom header

49. Slice Thickness slice thickness = 3.00 mm

53. Space Directions Extract the pixel size from the Dicom Header.

54. Space Directions Pixel size = 0.9375 mm x 0.9375 mm The dataset was acquired with Superior-Inferior slice ordering

55. 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 DICOM: LPS SLICER: RAS

56. Space Origin Courtesy G.Kindlmann 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.

57. Space Origin The space origin information is located in the Dicom header [ 0020,0032, Image Position Patient ] Courtesy G.Kindlmann

59. Space Origin Click Add Volume select the tab Props, and the format DICOM

60. Space Origin Click on Select DICOM Volume Select the directory / FirstSlice containing the first slice

61. Space Origin Click on List Headers to display the content of the header of the first image.

62. Space Origin Slicer displays the content of the header of the first image.

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

64. Space Origin [0020,0032, Image Position Patient ] = -125.0, -124.09, 79.30

65. Space Origin Click on OK to close the Dicom Header Window

66. Space Origin --origin "( + 125.0, + 124.10,79.30)" Add the field origin to the unu command DICOM: LPS SLICER: RAS

67. Measurement Frame

68. Measurement Frame

70. Axis Ordering Courtesy G.Kindlmann

72. Output File Add the field output to the unu command --output myNrrdDWI.nhdr

73. Output File Type ls in the Tk Console The file myNrrdDWI.nhdr is listed in the directory

74. Acquisition parameters Open the file MyNrrdDWI.nhdr with a text Editor

75. Acquisition parameters Open a web browser at the location http://www.na-mic.org/Wiki/index.php/Dartmouth-DWI-parameters

76. Acquisition parameters Copy the acquisition parameters from this wiki page to the end of the file MyNrrdDWI.nhdr, hit Enter and save the resulting file

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

79. Loading the Nrrd Volume Click on Cancel to come back to the Main Menu

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

81. Loading the Nrrd Volume Select Nrrd Reader in the Properties field The Props Panel of the module Volumes appears.

82. Loading the Nrrd Volume 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

83. Loading the Nrrd Volume Slicer loads the Nrrd DWI dataset Left-click on Or and change the orientation to Slices

84. Loading the Nrrd Volume Change the FOV to 2000

85. Loading the Nrrd Volume The sagittal and coronal viewers display the 14 DWI volumes: 2 baselines and 12 gradients

86. Loading the Nrrd Volume Display the axial and sagittal slices inside the viewer. Use the axial slider to observe the baselines and gradient volumes.

87. 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

88. Converting the DWI data to tensors Slicer displays the anatomical views of the Average Gradient volume.

89. 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

90. Glyphs Orientation of the glyphs in the Corpus Callosum