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I think there are some deep learning approaches out there that try to infer a high-resolution volume from low resolution volumes in multiple planes.  I don’t know if they would work with only axial and sagittal images though. 


Matt.

 

From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Michael Mc Laughlin <michael@thecurate.com>
Reply-To: Freesurfer support list <Freesurfer@nmr.mgh.harvard.edu>
Date: Friday, March 31, 2023 at 6:36 AM
To: Freesurfer support list <Freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] Is it possible to add additional T1 scans to improve surfaces/segmentation

 

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I am working with standard neuro radiological MRI scans. 

 

These typically have something like this::

 

a)  T1 headscout volume: 1.6mmx1.6mmx1.625mm   160x160x128

b)  T1 se tra 0.72x0.72x5.2 320x320x30

c)  T2 tse tra scan 0.72x0.72x5.2 320x320x30

d)  T2 FLAIR (dark fluid) scan  0.58x0.58x5.2 460x460x30

c)  T1 tse sag 0.72x0.72x5.2 320x320x30

c)  T2 tse sag 0.72x0.72x5.2 320x320x30

 

I have found that the best results are obtained if I do the following:

 

i) Start with the T1 headscout volume: 1.6mmx1.6mmx1.625mm 

This produces poor pial results but much better than using the T1s with a small number of slices.

ii) Add in the flair data: Use -FLAIR and -autorecon3 with a FLAIR MRI scan

This dramatically improves the pial surfaces and they look almost normal

iii) Add some T2 data.

This give more improvement of the pial surfaces

 

See attached image for how the cortex looks after these stages

 

My questions are: 

 

1) How can I add in the data from the higher resolution T1 scans? (with only 30 slices)

 

2) If I add a second T2 scan with -T2 -T2pial -autorecon3  will the results improve even more?

 

 

Regards,

Michael

 

 

 

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