Hi Congying,
I’ve been a little separated from the coding on SIRF over the last few months, but I don’t believe the MHKEM has been incorporated into SIRF. The development required would not be particularly huge
(I think?). Although it would probably require some C++ level changes in SIRF to support the vector of anatomical images.
However, it is all up and running in the STIR engine itself. I’d suggest you have a go with STIR first.
Depending how familiar you are with STIR, I’d suggest first making sure you are able and comfortable to do a regular OSEM reconstruction. Once you’re happy there, it is very simple to try [M]HKEM,
see the example parameter file Daniel wrote here:
https://github.com/UCL/STIR/blob/master/examples/samples/KOSMAPOSL_mhkem.par
If you’re not so familiar with STIR, the User Guide is best to start. (Kris – the version on sourceforge is old, is there an updated version? I’ve attached my most recently compiled version, which
is a few weeks old just before 4.0)
You could use some of the publicly available information from the private Short Course run at MIC in 2018:
http://stir.sourceforge.net/MIC2018ShortCourse/main.htm
https://github.com/UCL/STIR-exercises
Converting your own data from the scanner can be a bit tricky, here’s a starting point:
https://github.com/SyneRBI/SIRF/wiki/PET-raw-data
Cheers,
Ash
--
Ashley Gillman
Postdoctoral Research Fellow | CSIRO AEHRC
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From: SyneRBI Users list <[log in to unmask]>
On Behalf Of Cy Chu
Sent: Monday, 11 May 2020 8:19 PM
To: [log in to unmask]
Subject: About the MHKEM
Dear SIRF Team,
Recently, I have noticed that the HKEM method available in SIRF seems to be updated to MHKEM which could work with multiple anatomical priors simultaneously (https://github.com/UCL/STIR/pull/424/).
I am wondering whether this MHKEM approach has become available in STIR or SIRF? If the new approach is available now, is it possible to find an example of using it? I really want to try this kernel-based method with our mMR PET data.
Thank you very much.
With best regards,
Congying Chu
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