This is really interesting! And perhaps surprisingly doesn't trigger any immediate major technical red flags (as someone who has worked with MRI and phased array beamforming), as many HN HW articles do.
My only criticism from the tech video would be that they spend some time lauding the nanometer deflection sensitivity, which might lead some to believe that's indicative of the image resolution. It's not, and it's somewhat of a distraction -- that's just giving us amplitude information, which is comparatively less important than correlated time/phase across the 100k sensors. They do later on state ~mm resolution, which is still great!
Doppler and motion blur may be an issue (e.g. heart beating), as one slice requires a full ring of sequential exposures. But still way faster than MRI, so probably fine.
On a lighter note, it could seriously change the meaning of get FUCT (Full body Ultrasound Computational Tomography)!
MRI physicist here as well. I have a basic understanding of ultrasound, and this looks like an array of transducers organized to perform tomography, just as CT did for Xray.
However Ultrasound quality depends highly on transducer-skin contact.
Any physicists here to comment on the effects of sonar through liquid and the effects on image resolution and field of view?
This is precisely why you do it in water - the water-skin contact is effectively perfect, as is the water-transducer interface, and the body of water is easily characterizable; in effect you are scanning one large object that consists of a body of water that just happens to have a human body in it, and then extracting the body from that scan.
The water is a clever impedance matching trick. The contrast in density between air and human flesh is high, so the waves all reflect off the surface rather than penetrating and reflecting off the internal structures we care about.
That's why normally you're concerned with really good transducer contact (squeezing out any air) or use a gel to match impedance.
I'm a bit rusty on CT, but I'd guess the resolution is proportional to the total number of transducers in the array (e.g. larger sensing surface equals tighter resolution) since you're basically taking a Fourier transform of the incident wave.
This paper, “Whole Cross-Sectional Human Ultrasound Tomography”, goes into more detail.
https://arxiv.org/pdf/2307.00110
Notably, the lead author on that paper was a visiting researcher at midjourney last year.
Ultrasound researcher working on fast microvascular imaging here. Depends on the datarates, you can generally get pretty good blood flow data pretty fast, with <.5 seconds per slice if you do it with appropriate algorithms. A lot of this depends on motion though as you said, as the issue is generally getting a high-enough SNR (blood flow is generally 30-40 dB below tissue in energy, except for the biggest of vessels). Generally, higher frequencies have less of a separation between blood and tissue, but they have issue with attenuation. But I think with enough SNR (and with their element count that may indeed be possible), they could get pretty good blood flow data across the whole body.