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Thanks Richard (and Ashley)

Major step forwards I think!

Any reason why you say to reconstruct before getting the most recent version of SIRF? (I hope not!)

kris

From: CCP-PETMR Developers list <[log in to unmask]> On Behalf Of Brown, Richard
Sent: 12 December 2019 18:06
To: [log in to unmask]
Subject: MR geometrical information

Hi all,

You may be aware of a problem that was plaguing us for a long time - the conversion of MR images (ISMRMRD and Gadgetron) to other SIRF image types (e.g., NiftiImageData and STIRImageData).

We think we’ve finally cracked it (massive thank you to Ashley Gillman!), so please give it a go and let us know if it works for you.


Suggested code to compare to the vendor reconstructed DICOM:

Step 0. Reconstruct your MR data.

Step 1: Pull the master branch of SIRF

Step 2: Convert:

import sirf.Gadgetron as g
import sirf.Reg as r
image_h5 = g.ImageData(‘image.h5’)
image_nii = r.ImageData(image_h5)
image_nii.write(“output.nii”)

Step 3: Compare with the vendor DICOM in your favourite viewer!


We think we’re ~half a voxel out for 3d acquisitions, so let us know if that’s true for you (and in which directions we’re out).


With any luck this will not only be useful for synergistic reconstruction, but I think it also might be the first .h5 -> .nii converter out there, so should be useful all by itself, too!


Happy SIRFing,
Richard

Research Associate in Medical Imaging Physics at University College London,
Institute of Nuclear Medicine, UCL Hospital, Tower 5,
235 Euston Road, London NW1 2BU, UK

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