SS3T-CSD released

[thijsdhollander]

Hi again @rutgerfick and others,

This is not so much an "issue" as just a small announcement, that might be of use for some of your developments here! So as the title implies, SS3T-CSD is now also "publicly" released from my end. Related, the 2019 version of the response function calibration (for either multi-shell as well as single-shell data) now also comes with it. The latter improves on the 2016 version mostly on the single-fibre white matter front, and while at it, delivers quite an improvement in speed as a bonus. Just a few sources, should it come in handy in any possible way:

• Release is a fork of mrtrix, called "MRtrix3Tissue"; all info on this website: https://3tissue.github.io
• Some release info (because this incorporates all mrtrix developments since RC3 as well, so about 1.5 years...): https://3tissue.github.io/doc/install/release.html (mostly if you need to know about changed command names)
• SS3T-CSD information (this will mostly interest you, I reckon): https://3tissue.github.io/doc/ss3t-csd.html . Note this now also includes a weighting mechanism for b=0 images. This is (part of the) key to controlling the "speed" of the algorithm somewhat. I noticed at some point your notebooks, basically finding what I was looking at every since the initial abstract, i.e. that the algorithm is best "stopped" at a certain point. So this version deals somewhat with that aspect. Note that the goal is also not to reproduce MSMT-CSD results at all times anymore: there's cases where SS3T-CSD fits the high b-value signal itself better if other shells don't come into play. This can lead to interesting findings ( https://www.biorxiv.org/content/10.1101/629873v1 ).
• New response function calibration is mentioned on that page too, but the essential information sits in the abstract ( https://www.researchgate.net/publication/331165168_Improved_white_matter_response_function_estimation_for_3-tissue_constrained_spherical_deconvolution ) and the ISMRM 2019 talk for some added visual intuition ( https://youtu.be/7yPSFgLt8CA ).
• Both response function calibration and SS3T-CSD are open source Python scripts, if you need any details on how things are exactly done in practice; though these scripts rely heavily on calling mrtrix commands (so might not be all that pure Python-readable, if that makes sense).

Note the SS3T-CSD implementation, while being exactly the mechanism of the 2016 abstract, does switch things a bit around in terms of what "delineates" an iteration (it starts with an "initialisation", which is essentially half an iteration, and then starts counting the next iteration as "iteration 1"). And then there's the added weighting of course as well.

I'll probably drop a bit of a wider announcement on Twitter or something within the next 24 hours; but I thought you might want to be among the first to have access to all info regardless. ;-)

Cheers,
Thijs

[rutgerfick]

Hi @thijsdhollander!

Thank you for this very nice announcement - I was honored to be among the first to know - and thank you for your patience for my reply!

I was waiting specifically for the publication of the Dmipy journal paper to respond to your issue, see https://www.frontiersin.org/articles/10.3389/fninf.2019.00064/full. As you will see, the implementation of your SS3T-CSD algorithm using Dmipy is the cherry on the cake for the Dmipy MC-model demonstrations ;-)

There is a lot to learn from the references you list in your suggestions, and I will discuss the best way to proceed on our end w.r.t. the implementation of the tissue response estimation. Thanks again for letting us know about your great advancements in this important matter!

Rutger

[thijsdhollander]

Hey Rutger,

No worries at all! Great seeing your publication out: just took a look, and it's really nice indeed. Dmipy really is a very well designed and considered toolbox; you've generalised the logic around multi compartment models very well. In that respect, apart from just a great piece of software, I reckon it's also a powerful prototyping tool; it literally speaks the language of multi compartment models at that very useful level of abstraction. And indeed, putting together the building blocks of SS3T-CSD fits well with that. Great stuff!

There's a few bits and pieces above indeed; they're also not per se all "issues", more updates and a bunch of references. Feel free to close this "issue" itself of course; the info is there for reference if/when it comes in handy. 😉

Cheers,
Thijs