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Whole-body magnetic resonance imaging at 0.05 Tesla

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Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#41

Post by nullc »

eig wrote: post #24

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 state of the art MRI stuff uses "compressed sensing" -- essentially image completion in some domain or another. Presumably, carefully designed to not hallucinate details or one would hope.

There isn't necessarily a particularly neutral choice here: the MRI scan isn't in the pixel domain, artifacts are going to be 'weird' looking-- e.g. edges that move during the scan ringing across the whole image.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#42

Post by Aurornis »

The idea sounds great, but the examples they provide aren’t encouraging for the usefulness of the technique:

> The brain images showed various brain tissues whereas the spine images revealed intervertebral disks, spinal cord, and cerebrospinal fluid. Abdominal images displayed major structures like the liver, kidneys, and spleen. Lung images showed pulmonary vessels and parenchyma. Knee images identified knee structures such as cartilage and meniscus. Cardiac cine images depicted the left ventricle contraction and neck angiography revealed carotid arteries.

Maybe there’s more to it that I’m missing, but this sounds like the main accomplishment is being able to identify that different tissues are present. Actually getting diagnostic information out of imagining requires more detail, and I’m not sure how much this could provide.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#43

Post by teaearlgraycold »

atoav wrote: post #29
eig wrote: post #24

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…

This is one aspect about machine learning models I keep discussing with non-technical passengers of the AI-hype-train: They are (in their current form) unsitable for applications where correctness is absolutely critical.

I don’t know enough to make absolute statements here, but deep learning models can beat out human experts at discerning between signal and noise. Using that to guess at data and then hand it off to humans gives you the worst of both worlds. Two error probabilities multiplied together. But to simply render a verdict on whether a condition exists I’d trust a proven algorithm.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#44

Post by GaylordTuring »

sieste wrote: post #32
BobbyTables2 wrote: post #30

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.

> Imagine going to a restaurant, ordering French onion soup, and getting a bowl of brown food coloring in water. Welcome to England!

[flagged]

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#45

Post by nullc »

jahnu wrote: post #19
ChrisMarshallNY wrote: post #11

Earlier quoted context omitted.

Also, they need to keep vats of liquid helium around. Difficult stuff to store. I knew they needed cold gas, but liquid helium is crazy.

There was some buzz years ago about using liquid nitrogen instead but I don’t know if it made it into widespread production https://www.wired.com/story/mri-magnet-cooling/

Sounds like that's more about using a cryocooler to minimize the helium used-- but presumably that requires keeping the coils in a particularly hard vacuum to adequately insulate them.

There is some research towards operating at liquid hydrogen temperatures -- but hydrogen has its own logistical challenges.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#46

Post by vhcr »

BobbyTables2 wrote: post #30
eig wrote: post #24

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.

Where do you draw the line? RAW, HDR, photo stitching, blur removal?

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#47

Post by peddling-brink »

eig wrote: post #38
BobbyTables2 wrote: post #30

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.

An MRI machine is a fancy 3D camera. Is this "3D Deep-DSP Model" so different from the processing Samsung did on their phones?

Samsung would replace a white circle with an image of the moon. Even calling it AI was a stretch.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#48

Post by sitkack »

The application of a system like this could be as augmentation to imagers like CT and ultrasound. Because of its up resolution techniques and lower raw resolution (2x2x8mm), it might not be used for early cancer detection. But it looks really useful in a trauma center or for guiding surgery, etc. These same techniques could also be applied to CT scans, I could see a multi sensor scanner that did both CT and NMRI use super low power, potentially even battery powered.

Regardless, this is super neat.

> We developed a highly simplified whole-body ultra-low-field (ULF) MRI scanner that operates on a standard wall power outlet without RF or magnetic shielding cages. This scanner uses a compact 0.05 Tesla permanent magnet and incorporates active sensing and deep learning to address electromagnetic interference (EMI) signals. We deployed EMI sensing coils positioned around the scanner and implemented a deep learning method to directly predict EMI-free nuclear magnetic resonance signals from acquired data. To enhance image quality and reduce scan time, we also developed a data-driven deep learning image formation method, which integrates image reconstruction and three-dimensional (3D) multiscale super-resolution and leverages the homogeneous human anatomy and image contrasts available in large-scale, high-field, high-resolution MRI data.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#49

Post by falcor84 »

zarmin wrote: post #34
BobbyTables2 wrote: post #30

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.

It's kinda like the classic Ebay scam where you buy a picture of the item instead of the item.

Yes, or the increasingly common Amazon one, where you get an AI-generated summary of the book, instead of the actual book.

Re: Whole-body magnetic resonance imaging at 0.05 Tesla

#50

Post by falcor84 »

eig wrote: post #28
alwa wrote: post #12

I can’t access the full paper, but from the abstract, is it accurate that they’re using ML techniques to synthesize higher-quality and higher-resolution imagery, and that’s the basis for their claim that it’s comparable to the output of a conventional MRI scan? Do clinicians really prefer that the computer make normative guesses to “clean up” the scan, versus working with the imagery reflecting the actual measurement…

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.
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