Please refer to change log for latest changes to TORTOISE. If you intend to use these correction measures, you will have to use 3.1.3 or above versions for all import and DIFFPREP processing as well. They are the gradient non linearity correction. Note: Two additional parameters have been introduced in DRBUDDI3.1.3 and above versions, which were not present in the 3.0 version. These are the inputs to DR-BUDDI together with the structural image (for best results, it is best to use a T2 W fat suppressed dataset). Under 3.2, if the tag -do_not_use_structural 1 is used, then the structural provided will only be used as a reorientation template for the final output corrected data.Īn example scenario: If you have a test dataset with Subject1_DTI_UP (blip up) and Subject1_DTI_down (blip down), both will have to go through DIFFPREP processing separately to generate Subject1_DTI_up_proc.list and Subject1_DTI_down_proc.list that are generated within each of the up and down proc folders. If the structural data is subpar, DRBUDDI 3.2 can be run without it and utilize the information from the blip and down DWI data. The latest version of TORTOISE ver3.2 has capability to run DRBUDDI without a structural data. If you need further assistance with the settings please contact the TORTOISE support team. If the results do not look satisfactory, you may change few of the advanced settings to fine tune. Other advanced settings listed in the help file are incorporated in the run and used internally. The only inputs required are blip up data proc.list, blip down data proc.list, an anatomical image-preferrably T2W fat suppressed image. If you have acquired data with opposite phase encoding direction, please skip the EPI correction in DIFFPREP and do the DRBUDDI correction as described below.It is adviced that DRBUDDI be first run with the default settings. DR-BUDDI performs EPI distortion correction using two datasets with opposite phase encoding directions.
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