Questions and answers:
- What is JDTI?
- How do I download JDTI?
- How do I install JDTI?
- I am interested in JDTI. What kind of documentation do you have available?
- What kind of information could be gained from maps of tensor-related parameters?
- What kind of hardware / software is required to use JDTI?
- What kind of imaging data is needed to use JDTI?
- What kind of user input will be needed to use JDTI?
- What methods does JDTI use?
- How can I be sure that JDTI was correctly installed?
- How do I upgrade to the new JDTI version?
- Where can I get support, discuss issues related to JDTI, or discuss issues related to diffusion tensor MR imaging in general?
- What is the easiest way to stay informed about new software releases?
JDTI (pronounced “Jay Ditty”) is a Java software tool designed to analyze diffusion tensor imaging (DTI). JDTI is implemented as a plugin to ImageJ, an open source image analysis program (rsb.info.nih.gov/ij/). This software is being offered as a research tool for individuals affiliated with industrial or academic institutions.
DTI produces three different diffusion-related images, and also two masks:
- ADC is the apparent diffusion coefficient map, a measurement of the general tendency of water protons to diffuse in the underlying voxel
- FA is the fractional anisotropy map, a measurement of whether water proton diffusion is equal in all directions (low anisotropy) or whether diffusion proceeds preferentially in certain directions (high anisotropy).
- Directional map is a color map of the primary direction of diffusion (red is right to left, green is top to bottom, and blue is perpendicular (normal) to the plane of the slice.
In addition the brain mask and fractional anisotropy masks used to make these images are produced.
Of note, at the present time, JDTI does not perform fiber tract mapping.
- Fill out the Leave a Reply form on this page with your name and email address.
- In the Comment section, enter your institution name and mention that you would like to download JDTI.
- Click the Post Comment button. Your comment will be submitted to us but will not be published on the website.
- You will receive an email with the link to where you can download the JDTI software and related files.
- Read and abide by the software disclaimer:
Copyright ? 2004-2006 by Duke University. All rights reserved.
Permission to copy, use, and modify this software and accompanying documentation for educational and research purposes is hereby granted, without fee and without a signed licensing agreement, provided that the above copyright notice, this paragraph and the following two paragraphs appear in all copies including derivatives of the software. The copyright holder is free to make upgraded or improved versions of the software, provided that they are made readily available to others on these same terms without fee or any other charge. Contact the copyright holder at email@example.com for commercial licensing opportunities.
IN NO EVENT SHALL THE COPYRIGHT HOLDER BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OF ANY KIND WHATSOEVER, ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF HE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
THE COPYRIGHT HOLDER SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE AND ACCOMPANYING DOCUMENTATION IS PROVIDED “AS IS”. THE COPYRIGHT HOLDER HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS
- In any publication using JDTI software, cite this lab’s website:
Make a directory called JDTI in your ImageJ plugins folder and unzip the downloaded files (JDTI-1.5.zip and DBLAB_2.0.zip) into this subdirectory, and then restart ImageJ.
Important: If you have already installed TOPPCAT and/or DSCoMAN, please replace the DBLAB.jar file you are presently using with the one available with JDTI.
- A User’s Guide to JDTI is available here.
- JDTI test data instructions are available here.
- JDTI release notes are available here.
- The JDTI dashboard is available here.
- Detection of white matter infiltration by neoplastic disease including cerebral gliomas.
- Evaluation disease burden in patients with multiple sclerosis, where elevated diffusivity has been reported in white matter which appears normal on conventional T2-weighted MR images.
- Evaluation of patients with ischemic cerebral white matter disease, including CADASIL (cerebral autosomal dominant arteriopathy
with subcortical infarcts and leukoencephalopathy) and ischemic leukoaraiosis
- Measurement of white matter involvement in diseases such as ALS (amyotrophic lateral sclerosis), Alzheimer’s disease and HIV.
- Evaluation of patients with white matter disease such as Krabbe’s disease and X-linked adrenoleukodystrophy.
JDTI is designed to run on hardware running an operating system that supports ImageJ, a public domain open source Java-based image processing program authored and maintained by Wayne Rasband at the National Institute of Mental Health (rsb.info.nih.gov/ij/). Supported operating systems include Mac, Windows, UNIX and Linux platforms.
Be aware that the processing of JDTI is a processor and memory intensive task. The resources needed to process these images vary depending on the size of the data sets involved. For large data sets, it helps to set the memory requirements of ImageJ correctly and install additional RAM if needed.
JDTI uses diffusion tensor images as input. A set of DTI images is generally arranged as a number of passes (usually at least six different diffusion gradient passes, and one pass obtained without a diffusion gradient).
The user input required is:
- The b value of the diffusion gradients and directions they were applied.
- Thresholds used to create mask images for the tissue of interest (map values are not calculated for locations where the pixel intensity on B0 images is lower than the threshold value) and for lower limits of fractional anisotropy to be displayed in the tensor directions map. These clean up the visual appearance of the images, but can be set to zero if no thresholding is desired.
Please see the JDTI user’s guide.
To test that JDTI was correctly installed:
- Click the “Download the test data” link found in the JDTI Software section on the right. Please note that this information is available only to the registered JDTI users.
- Download the zipped package of test data and save into a temporary directory.
- Copy TensorDirections.txt and save it in main ImageJ directory.
- Open the test image data (test20050901.tif) in ImageJ.
- Open the test macro (JDTItestmacro.txt) in ImageJ.
- Run the macro (click on the test image data which makes it active, then click on the macro and press control-R)
- The resultant images should match (i.e. ADC = ADCtest.tif, FA = FAtest.tif, etc)
First delete all the class files belonging to the old JDTI version from your ImageJ plugins folder. Then download and unzip the new JDTI software into the subdirectory JDTI under your ImageJ plugins folder. JDTI 1.5 depends on some Utility classes that can be obtained by clicking on the “Download the Utilities” link under the JDTI software tab. Unzip the Utilities file DBLAB_2.0.jar into the main ImageJ plugins folder i.e. ImageJ_Home\plugins where Image_Home is the home directory of your ImageJ installation. This will save the DBLAB.jar into the main plugins folder. If you already have an existing DBLAB.jar from the Dan Barboriak lab in your ImageJ\plugins folder, overwrite it with this new one.
Where can I get support, discuss issues related to JDTI, or discuss issues related to diffusion tensor MR imaging in general?
- By email: Click on the “Contact Us” link on the left side of the lab homepage. In the Comments field type in keyword “Mailing List,” and we will send you periodic email about software upgrades available from the lab, as well as other news. Let us know if you would like to be taken off of the mailing list.
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