I've written my first (useful) python script, a small program called convertDICOM2AFNI.py, that looks for DICOM files from our scanner and converts them to AFNI format. Converting raw scanner data to AFNI format using the to3d command is light years (i.e., minutes) faster than SPM's DICOM import, or MRIcron's dcm2nii program. dcm2nii, in particular, usually gave me a bunch of other files that I was never interested in and would convert everything in my raw DICOM folder, even though there were only a few runs that I was interested in looking at. It would also introduce some weird temporal interpolations into the data, modifying the header information to make it appear as though the volumes were slice-time corrected even though they actually were not.
In order to get around this problem, I may add an option to the script which converts to AFNI, and then converts to nifti format using 3dAFNI2NIFTI (although I have no idea what might get lost in the translation; will need to do some testing here).
To use the script, do the following:
1) Create folder containing all raw DICOM files generated from your experiment
2) Write down which session numbers correspond with which functional and anatomical runs (remember: pencil & paper are your friends)
3) Run the script from the raw DICOM directory using the command "python convertDICOM2AFNI.py"
It will ask you a series of questions about which session numbers are your functional runs, and then which session is your anatomical run. If you run the command without defaults (i.e., without using the "-d") flag, it will also ask you the number of slices in the z-direction, the number of TRs, and the length of each TR in milliseconds.
In the future, I plan to have the program automatically read in a defaults file that specifies all of these arguments automatically. However, that also assumes that the user is organized (which I am not). Also, as of this writing, it assumes that the z-slices alternate positively in the z-direction; if this is not true for you, you may need to change the script yourself.
The script is available for download over at my webpage (http://mypage.iu.edu/~ajahn) under "Python Scripts". The actual location of the scripts I write will probably change as I become more organized.
I plan to begin writing a suite of Python programs that I find useful for interacting with both SPM and AFNI data, eventually working up to a GUI sometime in the far future. For now, it will assume a degree of command line proficiency and that you can probably figure things out if the script does not perfectly fit your needs.
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Due to high demand from the Scottish population at IU, a screencast will soon be up detailing how to interpolate volumetric data onto a template surface.
In order to get around this problem, I may add an option to the script which converts to AFNI, and then converts to nifti format using 3dAFNI2NIFTI (although I have no idea what might get lost in the translation; will need to do some testing here).
To use the script, do the following:
1) Create folder containing all raw DICOM files generated from your experiment
2) Write down which session numbers correspond with which functional and anatomical runs (remember: pencil & paper are your friends)
3) Run the script from the raw DICOM directory using the command "python convertDICOM2AFNI.py"
It will ask you a series of questions about which session numbers are your functional runs, and then which session is your anatomical run. If you run the command without defaults (i.e., without using the "-d") flag, it will also ask you the number of slices in the z-direction, the number of TRs, and the length of each TR in milliseconds.
In the future, I plan to have the program automatically read in a defaults file that specifies all of these arguments automatically. However, that also assumes that the user is organized (which I am not). Also, as of this writing, it assumes that the z-slices alternate positively in the z-direction; if this is not true for you, you may need to change the script yourself.
The script is available for download over at my webpage (http://mypage.iu.edu/~ajahn) under "Python Scripts". The actual location of the scripts I write will probably change as I become more organized.
I plan to begin writing a suite of Python programs that I find useful for interacting with both SPM and AFNI data, eventually working up to a GUI sometime in the far future. For now, it will assume a degree of command line proficiency and that you can probably figure things out if the script does not perfectly fit your needs.
===============================
Due to high demand from the Scottish population at IU, a screencast will soon be up detailing how to interpolate volumetric data onto a template surface.