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| − | 0. Overview
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| − | 0.1 Requirements
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| − | 1. Run agconvert to overlay images
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| − | 2. Modify patient names for unique files.
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| − | 4. Load data into InstaTrak
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| − | '''0) Overview'''
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| − | This process is used to prepare fMRI images for use in the InstaTrak surgical guidance system. fMRI images are processed in the Analyze format used by SPM, but the InstaTrak only supports DICOM images. To use fMRI data on the InstaTrak we overlay the fMRI onto a structural image series, and then write the series in DICOM format. This series may then be loaded and fused on the InstaTrak.
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| − | The agconvert matlab script does all of these tasks, optionally running the initial coregistration.
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| − | '''0.1) Starting point'''
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| − | This document presumes the existence of the following:
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| − | :- fMRI dataset processed using SPM: patients/AG_####/SPM_analysis/{tasks}/SPM.mat
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| − | :- thresholded fMRI activation map: patients/AG_####/SPM_analysis/task/task_t6.img
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| − | :- target structural image in Analyze format AND corresponding DICOM-format original series.
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| − | this should be in: AG_####/SPGR/SPGR.img or AG_####/T2/T2.img
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| − | and: AG_####/raw/lisa_dicoms/0000##.SER/000001 - 000###.IMG
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| − | '''1) Run agconvert to overlay the images
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| − | Start matlab and SPM
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| − | # matlab
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| − | >> spm fmri
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| − | From the SPM "Toolboxes" menu, select "agconvert." (note: if agconvert not listed, try typing "agconvert" at prompt)
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| − | agconvert should display an interface entry buttons. Fill in the "Subject ID:" field as appropriate, either AG_#### or simply #### (the script will complete).
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| − | "anatomical file"
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| − | Browse to select the target structural image. This should generally be a T2 or SPGR series, or occasionally a FLAIR. The img/hdr pair should be found in AG_####/SPGR etc.. If no appropriate image is available, you will need to [[nsg:mricro|convert the DICOM series]] using mricro.
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| − | NOTE 1: Proper image alignment must be maintained. It is necessary to
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| − | NOTE 2: the VTI system will not properly segment an image series larger than 150 slices. Usually we can get around this: [[cut off the bottom of an image|nsg: make smaller image
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