Functional Ultrasound Imaging (fUSI) from scratch | Hacker News Reader

Functional Ultrasound Imaging (fUSI) from scratch

neuroai.science

54 pointspminimax11 comments

How do you propose to solve the “rigid skull” problem (footnote 2 in the post)? Most people like having theirs intact during diagnostic imaging.

I await clinical use of this with bated breath…

Merge labs (previously Forest Neurotech) is starting with people who have a certain surgery that needs excising a window in the skull -- and using that as an acoustic window. And in parallel hoping to figure out sufficiently good imaging across the skull for the general user.

There was also an exciting fUS imaging demo from Aleph neuro a few months ago.

I wonder if you could image through the eyeballs? Someone must have tried it

Very interesting, great write up, and awesome blog in general!

I never got to invest serious time in this idea, but MMW: trimodal EEG+fNIRS+fUSI dry headsets are going to change everything. Each technique has its strengths, and there are already people hacking together trimodal prototypes as we speak.

That's cool. Ultrasound imaging should be much more broadly available, like household object next to your toothbrush. I wonder how OpenWater open-source focused ultrasound stimulation is doing.

I've recently built my own ultrasound machine at home with only the probe being an ebay buy from a previously working machine.

I've gotta get on writing an article about it one day!

Please do! That makes me wonder how hard it would be to make a probe.

Well done, although all commercial ultrasounds are just a probe (piezoelectric curved or linear array) connected to a computer, previously over a high speed custom parallel bus, today USB-C will do. Then M-mode or B-mode reconstruction just runs in software. Doppler needs beam-steering etc and is a bit more complex.

Oh, I have some ultrasound probes lying around - would be very interested in a report!

Cool stuff :)

What's the relationship between the blood flow and energy use? I know fMRI uses BOLD which then has an IIRC ~6s expected pattern that you apply as a convolution on the data, as it's looking at the oxygenation of the blood. Here it's energy use -> vasodilation -> change in blood flow - what's the relationship like between those?

The engineering is impressive. The actual information you get out of the technique feels considerably less so.

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