91–100 of 159 posts
Earlier quoted context omitted.
The Samsung phone wasn’t a technological advancement, it was sheer fraud. A camera is supposed to take pictures of what it sees. Imagine going to a restaurant, ordering French onion soup, and getting a bowl of brown food coloring in water.
Where do you draw the line? RAW, HDR, photo stitching, blur removal?
Earlier quoted context omitted.
I'm a professional MR physicist. I genuinely think the profession is hugely up the hype curve with "AI" and to a far lesser extent low field. It's also worth saying that the rigorous, "proper" journal in the field is Magnetic Resonance in Medicine, run by the international society of magnetic resonance in medicine -- and that papers in nature or science generally nowadays tend to be at the extreme gimmicky end of the…
Would it be easier to deploy devices like this to developing counties without the infrastructure to support liquid helium distribution? I imagine a much simpler device WRT exotic cooling and distribution of material requirements is a plus. Couple that with the scarcity and non-renewable nature of helium, maybe using devices like this at scale for gross MRI imagery makes sense? The AI used here as I read it is a gener…
The cold head vibration can introduce a bit more B0 drift per day, but it's not practically a problem.
Regarding artefacts, one of the other reasons that MRI rooms are expensive are the Faraday cages. They do help. Not just in terms of noise floors but because there tends to be a lot of intermittent RF transmission from people like paramedics. Did you know a) that the international mayday frequency is 121.5 MHz, b) that overhead helicopter flights may transmit with kW of RF on that frequency, c) that the larmour frequency of protons at ~2.9T is 121.5 MHz, d) that Siemens "3T" magnets are routinely around 2.9T, and e) the voltage of the signal you detect in MR is micro to millivolt at best? I've seen spurious peaks in spectra from this.
The DL method the paper talks about "may work", but as the OP says this is deeply unsatisfactory for a whole host of reasons and is, in my overly sarky opinion, a bit like fixing a wall with rising damp by putting a television in front of it showing a beautiful, high resolution picture of a brick wall in the same colour.
Earlier quoted context omitted.
I don't think we know what's in the black box here. It could be an equivalent relatively unopinionated regularizer ("the pixel domain will be locally smooth, to the extent it has edges they're spatially contiguous") or it could be "just look up the most similar image from a library and present that instead" or anywhere in between. :)
They specifically said they use deep learning which implies a sizeable neural network.
Earlier quoted context omitted.
It would suck if lesions or tumors look like noise.
Except there are other uses for an MRI and something that doesn’t require super conductors would be pretty awesome and deployable to places that lack the infra to support a complex machine depending on near absolute zero temperatures and the associated complexities.
If the technique is fundamentally broken, then it won't work in any situation.
A few months ago there were articles going around about how Samsung galaxy phones were upscaling images of the Moon using AI [0]. Essentially, the model was artificially adding landmarks and details based on its training set when the real image quality was too poor to make out details. Needless to say, AI upscaling as described in this article would be a nightmare for radiologists. 90% of radiology is confirming the…
heads should roll etc
A few months ago there were articles going around about how Samsung galaxy phones were upscaling images of the Moon using AI [0]. Essentially, the model was artificially adding landmarks and details based on its training set when the real image quality was too poor to make out details. Needless to say, AI upscaling as described in this article would be a nightmare for radiologists. 90% of radiology is confirming the…
The Samsung phone wasn’t a technological advancement, it was sheer fraud. A camera is supposed to take pictures of what it sees. Imagine going to a restaurant, ordering French onion soup, and getting a bowl of brown food coloring in water.
Earlier quoted context omitted.
I can say that most radiologists would not want a computer trying to fix poor scan data. If the underlying data is bad, they would have recommend an orthogonal imaging abnormality. "I don't know" is a possible response radiologists can give. Trying to add training data to "clean up" an image would bias the read towards "normal".
To nitpick, wouldn't it by definition bias the read toward normal? I suppose the problem is more that you don't want to bias it to normal if it wasn't.
A few months ago there were articles going around about how Samsung galaxy phones were upscaling images of the Moon using AI [0]. Essentially, the model was artificially adding landmarks and details based on its training set when the real image quality was too poor to make out details. Needless to say, AI upscaling as described in this article would be a nightmare for radiologists. 90% of radiology is confirming the…
the future is already here, GE has put this into production. if you have remove the onerous constraint of being correct you can make some really crispy images! 9/10 radiologists. that was literally what the FDA approval process was, surveyed a bunch of radiologists to see what they preferred. no adults in the room. heads should roll etc