vo2anlz Down Load Page

Our “vo2anlz” can convert a diffusion tensor tractogram made by dTV to “analyze-format” which is compatible with navigation systems such as VectorVISION and Stealth Navigation System.

Diffusion tensor tractogram should be made by dTV and the tract must contain color not be black, white, or gray scale. First, the user should make a colored tractogram on a T2* weighted-image channel and then select “select all” from the Edit pull down menu in VOLUME-ONE. Then the user should click the ROI editor tab in dTV and select “voxelize tracking lines as color volume” from the pull down menu under Special in dTV. These procedures will superimpose the colored tract to T2* weighted images. At last the user should save the result as a VOLUME-ONE file, not a dTV file, by selecting “save” from File pull down menu in VOLUME-ONE. Our “vo2anlz” converts colored tract voxels in this VOLUME-ONE file to completely white voxels in the analyze-format file. The procedures are explained in detail in the next section. The saved analyzed-format file will consist of a ####.img and a ####.hdr file. Both files must be imported to the navigation system and then can be superimposed to the anatomical images. The user can confirm the result in the analyze-format file using free software such as MRIcro.

No guarantee, no warranty

Please use this at your own risk.

Requirements

How to use

For VectorVISION users
  1. Open terminal window or command window.
  2. Move to the directory which contain “vo2anlz” and the tractogram saved as a VOLUME-ONE file.
  3. Type “java -jar vo2anlz.jar -s 0.975 aaaa bbbb” and hit “return”
    Where “aaaa” is the user made file name of tractogram saved as a VOLUME-ONE file.
    And “bbbb” the user chosen file name of analyze-format, so please type as you like.
    “0.975” is the length of one side of the voxel in the VOLUME-ONE file. In our institute, the FOV is 240 mm in x- and y-axis and 120 mm in z-axis. The matrix of the tractogram saved as VOLUME-ONE file is 256*256*128, respectively. So the voxel is a perfect cube and the length of one side is 0.975 mm. So we use “0.975” here. If your file consists of different size voxels, please calculate the size (mm) relevant to your FOV and matrix.
  4. The bbbb.img and bbbb.hdr files will appear in the same directory.
For Stealth system users
  1. Open a terminal window or a command window.
  2. Move to the directory which contain “vo2anlz” and the tractogram saved as Volume-One file.
  3. Type “java -jar vo2anlz.jar -s 0.975 -8s aaaa bbbb” and hit “return”
    or
    Type “java -jar vo2anlz.jar -s 0.975 -7 aaaa bbbb” and hit “return”
    Where “aaaa” is the user made file name of tractogram saved as a VOLUME-ONE file.
    And “bbbb” the user chosen file name of analyze-format, so please type as you like.
    “0.975” is the length of one side of the voxel in the VOLUME-ONE file. In our institute, the FOV is 240 mm in x- and y-axis and 120 mm in z-axis. The matrix of the tractogram saved as VOLUME-ONE file is 256*256*128, respectively. So the voxel is a perfect cube and the length of one side is 0.975 mm. So we use “0.975” here. If your file consists of different size voxels, please calculate the size (mm) relevant to your FOV and matrix.
  4. The bbbb.img and bbbb.hdr files will appear in the same directory.

The output pixel options “–8s” and “–7” are described as follows. Please select one in which the contrast is better in your system.

output pixel options
-8 8-bits unsigned (default)
-8s 8-bits signed
-7 7-bits

Suggestions for successful autofusion

The colored tract should be as thin as possible. In our experience, using “autofusion”, pyramidal tracts were successfully superimposed to anatomical images in all but three cases. These three cases required manual fusion. Our software vo2anlz can convert colored pyramidal tract in dTV to completely white pixel in 8 bit analyze-format. It is highly improbable that MR images contain a large amount of completely white pixels, but such an extreme singular value might prevent successful “autofusion”. We found that the three images in which tract required manual fusion contained a large amount of completely white pixels. To compensate we made pyramidal tracts as thin as possible in order to limit the number of white pixels. Thereafter “autofusion” has successfully superimposed pyramidal tracts to anatomical images.

Acknowledgment

Without the work of Dr. Yoshitaka Masutani and Dr. Shigeki Aoki who kindly developed and freely distributed their software dTV and VOLUME-ONE, our project would not have been possible. Thank you.

　

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