Hi!

We are processing images using

recon-all  -all -3T -mprage -qcache -hippocampal-subfields-T1 -brainstem-structures

We've encountered an issue when we're trying to use multiple inputs (acquired at the same timepoint and with comparable quality). The issue is due to the two images having slightly different voxel sizes:

ERROR: MultiRegistration::

loadMovables: images have different voxel sizes.
  Currently not supported, maybe first make conform?
  Debug info: size(1) = 1, 1, 1.2   size(0) = 1.05469, 1.05469, 1.2
MultiRegistration::loadMovables: voxel size is different /tmp/adni/freesurfer/6.0.0/0a9cfea9-7668-4a2c-927c-378ff5109fe1/mri/orig/002.mgz.

which we can see confirm from the DICOMs in the PixelSpacing tag.

So, we have three questions:

1. In general, should using multiple images jointly for processing yield better results?
2. If so, what would you suggest for our case with images of two different protocols? Any flags that could help? Or perform coregistration pre-run?
3. Let's say we have a cohort where all subjects have two T1-images but where some subjects have two images acquired with slightly different protocols (e.g. different voxel sizes) and jointly processing can't be done. Do you think it is better to combine images in as many cases we can (and use only a single image for the remaining cases) or only use one image per case for all cases? In other words, we are wondering if it could bias our data set if the subset of that has been multi-image processed is "better" than those processed with only a single image.

We're running on FS6 (freesurfer-Linux-centos6_x86_
64-stable-pub-v6.0.0-2beb96c) and I've attached a log file from one of the failing cases.

Thank you for your help!

Best regards,

--
Gustav Mårtensson | PhD student
Division of Clinical Geriatrics
Department of Neurobiology, Care Sciences and Society
Karolinska Institutet
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Karolinska Institutet – a medical university