The super-resolution trick as they’ve done it is highly reliant on the sparseness of the bubbles. If you imagine a point or a very sparse set of points at low resolution, you can fit for the locations of those points even though you don’t see them clearly. This is a common technique in radio astronomy and (I assume although I don’t have personal knowledge) astrometry, and compressed sensing was an extremely hot field a while back.
But RBCs are weird squishy things, and they fill the bloodstream quite densely, and ChatGPT estimates that they’re spaced about 20µm apart and that, when confined to a capillary, they’re about 7µm long. (And that sounds at least plausibly correct to me.)
So, even ignoring the much worse scattering properties of RBCs, they not nearly as sparse. You mostly lose a whole dimension of sparseness and up trying to resolve the entire capillary. Which seems possible but much harder. Unfortunately, brain capillaries are about 40µm apart, so the result might be a mess.
The article did not say what wavelength they’re using or what their native (wavelength/2) resolution is.