[HN Gopher] A low-cost and shielding-free ultra-low-field brain ...
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A low-cost and shielding-free ultra-low-field brain MRI scanner
Author : innolitics
Score : 318 points
Date : 2022-02-04 15:35 UTC (7 hours ago)
(HTM) web link (www.nature.com)
(TXT) w3m dump (www.nature.com)
| omarhaneef wrote:
| Don't they already have something like this in the field?
| https://hyperfine.io
| wforfang wrote:
| This exact product is mentioned in the article as evidence for
| clinical/market demand. It also shows precedence for FDA
| approval of a pretty similar instrument for clinical
| diagnostics. Although, its interesting to note that the
| hyperfine MRI (at least ostensibly) seems to do the same thing
| in a smaller/more portable form factor.
| omarhaneef wrote:
| I missed it, but I guess my underlying question remains: what
| is the innovation over previous attempts that gets the paper
| into nature?
| SubiculumCode wrote:
| This is cool. Don't get me wrong. You could build this in your
| garage maybe. But those scans are useless for what I do in my
| research. The resolution and contrast it provides are just too
| low. Edit: for neuroscience research..I hadn't considered any
| clinical utility.
| m00dy wrote:
| well, I can call this is a research :)
| saulrh wrote:
| Being able to use this around metal is _also_ huge. It means you
| can use it on patients with metal implants or bullets in them, to
| guide surgery in real-time, in the surgical suite, at the same
| time as other medical instruments, at the patient 's bedside
| instead of in a dedicated room that you have to transport the
| patient to, etc.
| _qua wrote:
| People with metal implants and bullets can often still have
| MRIs with some additional screening/safety measures. There may
| be advantages to operating under live MRI guidance but I'm not
| aware of any research on that. Even with low fields, you still
| would get artifact from having metal near your target of
| imaging.
| lostlogin wrote:
| The images are better that I expected. The 'FLAIR like' image is
| not particularly FLAIR like. FLAIR are nicer to look at when fat
| saturated (not everyone agrees with that), but that's probably
| not feasible at that field strength and adding scan time would be
| a problem on these long sequences. Voxel sizes of 2x2x10 are
| pretty terrible resolution, but if the alternative is nothing, I
| guess that's ok. The static field is so low, I'm impressed it
| works at all.
| TheJoeMan wrote:
| You know, sometimes all you need is "do I have a baseball sized
| tumor or not".
| ska wrote:
| In that case, likely you found it before anyone asked for an
| MRI.
| [deleted]
| innolitics wrote:
| That's absolutely true. We work with a lot of technical
| founders who are turning their research into a diagnostic
| medical devices. One of the first questions we always ask is:
| how will the information produced by your device help
| clinical decision making? More data is _nice_ but if it
| doesn't alter the course of treatment, it's pointless.
| Sometimes it's okay if the doctor doesn't know if the problem
| is A or B if the treatment for A and B is the same.
| queuebert wrote:
| Or a massive brain hemorrhage.
| fluidcruft wrote:
| That's generally been the challenge with these super low-
| field scanners--they can't get T2*/susceptibility that's
| anywhere close to useful (yet?).
| mwint wrote:
| Reading the terminology being thrown around here, where
| could I go to get a basic understanding of what you'll
| are talking about?
|
| It sounds like different modes of taking (or
| interpreting/visualizing?) an MRI.
| rasmus1610 wrote:
| These are different MRI sequences that are weighted
| differently to produce a specific contrast that show
| different characteristics of the tissue that is imaged.
|
| I really liked ,MRI made easy' as an introduction to MRI
| physics. Just google it, it's a free Book
| lostlogin wrote:
| How funny, you just beat my comment. A link to it.
|
| https://rads.web.unc.edu/wp-
| content/uploads/sites/12234/2018...
| fluidcruft wrote:
| (vastly simplified) MRI basically functions on two
| fundamental mechanisms--"spin echo" and "gradient echo".
| Spin echo signal is described by T1 and T2. Gradient echo
| signal is described by T1 and T2*. The difference between
| T2 and T2* relate to local magnetic properties of the
| tissue which is called "susceptibility". Blood contains
| iron so its presence alters T2* and this is exploited
| clinically. A good example of T2* imaging used clinically
| is susceptibility-weighted imaging (SWI).
|
| T2* effects increase with higher MRI main field strength.
| From what I can tell so far these ultra low-field
| scanners have to rely on spin echoes.
| lostlogin wrote:
| I've spent a long time around scanners and re-read this
| book before helping students. It's remarkable easy to
| lose track of the fundamentals, though maybe that's just
| me.
|
| The whole book is available for free as a download. MRI
| Made Easy (... Well almost). https://rads.web.unc.edu/wp-
| content/uploads/sites/12234/2018...
| AnimalMuppet wrote:
| But if the answer is "yes", the next question is "do I also
| have pinhead-sized metastases, and if so, where?"
| car wrote:
| Those metastases get taken care of by chemo- or
| immunotherapy.
| littlestymaar wrote:
| Isn't this question answered by a PET scan and not MRI ?
| doctoring wrote:
| Usually not!
|
| PET scans are limited in resolution when you get down to
| the sub-5 mm or so range due to scanner technology and
| fundamental limits of the physics of positron/electron
| annihilation & photon emission.
|
| A typical MRI (i.e. alas, not what this article is
| describing) can usually resolve something at that size
| and identify characteristics like diffusion restriction
| or contrast enhancement which can confirm metastasis.
|
| Also, in the brain, PET scans (at least the most common,
| FDG, which is based on glucose) are extremely limited in
| utility because of the baseline high glucose metabolism
| of the brain, which makes it hard to distinguish from the
| metabolic activity of a tumor.
| fluidcruft wrote:
| The flip-side of that is that PET is vastly multiple
| orders of magnitude far more sensitive than MRI. So while
| PET may not be able to localize as well as MRI, it can
| detect smaller things if the targeting of the
| radioisotope is good.
| lostlogin wrote:
| Maybe the state of play has changed, as we scan for this
| indication in MR, not PET.
|
| Have you a link to something as my understanding is that
| small lesions are better found with MR?
|
| Or is this a rule that applies to high end research work
| and hasn't hit clinical practice yet? Maybe a limitation
| of the isotopes used clinically?
| lostlogin wrote:
| I am unsure of the exact state of play but believe that
| small mets (eg a few mm in size) are better seen with
| MRI. MR is probably easier to get than PET too.
|
| There are usually a few radiologists lurking here and
| they would have better knowledge than me (I'm an MR
| tech).
|
| https://appliedradiology.com/articles/diagnosing-brain-
| metas...
| mabbo wrote:
| This is precisely what saved my father's life last year.
|
| 16 years ago he had some kind of brain cyst. Totally benign.
| But as a follow up, the doctor ordered yearly MRIs, much to
| his annoyance.
|
| Last year those yearly routine MRIs spotted a brain tumor-
| before it had time to get dangerous or cause any damage to
| him. It was growing quickly though and was right near his
| eye. Quick surgery got it out.
|
| I want to live in a world where everyone has access to that.
| lostlogin wrote:
| A tumour can be a lot smaller than 1cm and cause issues. A
| pituitary microadenoma is an example, and this machine
| would struggle to show it.
|
| That said, I'd like a go. I suspect that with more samples
| (more time) you could get the resolution up.
| an1sotropy wrote:
| I think it is amazing that they're getting decent ADC maps -
| diffusion imaging is fundamentally about measuring how much the
| image gets dimmer (due to diffusion sensitizing gradients), so
| it's always running up against SNR limits. This is so darn
| cool.
| lostlogin wrote:
| It really is.
|
| For some reason it reminded me of the crazy project where
| some team used the earths field as the static field and
| _just_ added gradients and the RF stuff. I can't find the
| article I remember but this project looks similar and scans a
| capsicum rather than an apple.
|
| https://www.researchgate.net/publication/6956005_A_practical.
| ..
| qrian wrote:
| Can this also do fMRI? I'm already trying to build DIY fnirs
| machine for cogsci research but if this does fMRI too I might
| build this one too.
| hwillis wrote:
| > We have experimentally estimated in our preliminary study
| that the apparent T1/T2 values for gray matter and white matter
| were approximately 330/110 ms and 260/100 ms at 0.055 T (vs.
| 1300/110 ms and 830/80 ms at 3 T51) while CSF maintains long T1
| (>1500 ms) and T2 (>1000 ms).
|
| That's not particularly different from normal MRIs, and the
| achieved resolution is not that much worse than normal MRIs.
| The scans have lower contrast (and repeated/longer scans is one
| way to improve that) and using for functional imaging will make
| that worse, but honestly it doesn't seem to have suffered very
| much at all.
| qrian wrote:
| > First, these scanners rely on complex superconducting
| electromagnet/cryogenics designs and ever increasingly powerful
| electronics (including gradient and radiofrequency power
| systems) for fast imaging and/or advanced imaging features like
| brain functional MRI and diffusion tractography, yet routine
| clinical uses only necessitate a small portion of these imaging
| protocols.
|
| I guess this implies not?
| lostlogin wrote:
| That's talking about a conventional scanner, the article is
| about a permanent magnet and a more straight forward design.
| qrian wrote:
| I guess then I will have to wait for someone much more
| knowledgable in mechanical engineering than me to answer.
| Thanks for the input.
| carbocation wrote:
| This sort of technology offers a lot of value for understanding
| human health in the future.
|
| Right now, we (physicians) discourage people from getting tested
| outside of guidelines because we don't know what to do with
| incidental findings. But you could imagine that as a society, we
| would like to detect and understand these things, rather than
| just remain ignorant to them.
|
| Inexpensive technology like this could be perfect for performing
| large-scale studies with repeated sampling of volunteers over
| time, to gain information that can help the next generation.
| robwwilliams wrote:
| And perfect for very high false discovery rates and unnecessary
| downstream diagnostic burden and iatrogenic errors. Rather see
| a focus on new magnet technologies to reduce cost without loss
| if already marginal clinical MRI resolution.
| sfink wrote:
| > And perfect for very high false discovery rates and
| unnecessary downstream diagnostic burden and iatrogenic
| errors.
|
| ...which is exactly why the comment you're replying to says
| that physicians discourage them. That's missing the point;
| noisier devices are indeed not going to be great at improving
| the existing applications. But there's a whole world of other
| possibilities out there as long you don't _try_ to substitute
| questionable data for good. Like monitoring over time, or
| between-patients studies where you get additional
| significance from large numbers, or even just fishing
| expeditions where you see what the cheaper and more
| deployable stuff is capable of. Not everything needs the best
| and only the best.
|
| > Rather see a focus on new magnet technologies to reduce
| cost without loss if already marginal clinical MRI
| resolution.
|
| Why not both? The work required is going to be pretty
| different.
|
| And chaining them together is a time-honored technique: use
| the quick cheap thing to detect reasons to dig in with the
| fancy stuff. Your base rate may be low, but if the quick
| check is negative then the adjusted probability might drop it
| below some other cause that you'd be better off looking into.
|
| Data is good, just don't fuck it up.
| ratg13 wrote:
| When we say "low-cost", just how low cost are we talking here?
|
| I skimmed through the article, but still didn't comprehend how
| much something like this might actually cost.
| ska wrote:
| The up front cost is only one part of the story.
|
| Siting a conventional MRI is pretty expensive (often requires a
| new build 6 figures for sure) and operation costs can run up to
| even 5 fig/month for powerful ones.
|
| They could probably get one of these out the door for approx
| 100k. Clinical scanners are typically 10x+ that.
|
| Siting cost would be next to nothing, and operating costs low
| too.
| lostlogin wrote:
| This is a good comment and still underplays the cost of MRI.
| Getting a reasonable 3T setup going will be a lot more than
| US$1 million. Running costs are very high, with a scanner
| lifetime service contract being somewhere between 50% and
| 100% the original cost of the MRI scanner.
|
| Additionally, the scanner cost is only part the price. There
| is the Faraday cage, chilling, room setup, building
| strengthening, scanner install and shipping cost, peripheral
| equipment (compatible monitoring, injectors, compatible beds
| and chairs etc). It probably comes in at a doubling of the
| cost of the actual scanner.
|
| While reducing the cost of the install and running will help
| a lot, the staffing is the larger cost in radiology, as techs
| and radiologists are expensive.
|
| Costs will vary hugely depending on where you are in the
| world, but it isn't cheap anywhere.
| ska wrote:
| I was intentionally handwaving but above is about right in
| orders of magnitude, i just rolled things up.
|
| Staffing is an interesting one (which I ignored, but good
| point you can't really) - lots of potential deployments of
| a small machine like this probably don't look anything like
| a US standard imaging suite, and aren't going to be staffed
| the same way. If you run all the numbers in detail you get
| big variations here, depending on set up.
| gnatman wrote:
| Towards the bottom: "Such scanner can be made low cost to
| manufacture, maintain and operate. For quantity production, we
| estimate hardware material costs under USD20K."
| SubiculumCode wrote:
| That's cheap...just not cheap enough for me to want to build
| it in my garage as a party gag.
| datavirtue wrote:
| I have seen people of modest means build cars that cost
| five times that in their garage. ...and that was twenty
| years ago.
| ISL wrote:
| _Edit: This post was intended as a reply
| tohttps://news.ycombinator.com/item?id=30209618 , presently
| below_
|
| > _The lead author, Dr. Craig Bennett, wanted to get something
| fresh, so he headed in to the grocery story first thing in the
| morning. At the fish counter, he spoke the words that will echo
| down the centuries as a testimony to the dedication and drive of
| neuroscientists throughout the ages:
|
| >"I need a full length Atlantic Salmon. For science."_
|
| That reminds me of the day that I needed a strong lightweight
| cable for a silica-fiber melting/drawing apparatus. After some
| puzzling, I realized that bicycle shift/brake cabling would
| probably be perfect for the task.
|
| I'll never forget the puzzled look at the bike shop -- "What kind
| of bike are you putting it on?" "I'm not, I just need some brake
| cable for a science experiment...." As I recall, I think we
| finally settled on some precut cabling for a GT Zaskar of some
| kind.
|
| Similar things came up the day that I needed a valve that
| switched faster than our dedicated micro-switching valves. A
| similar light-bulb went on, and I went down to the nearby auto
| shop for a fuel-injector.
|
| "What kind of car do you need it for?"
|
| "I don't, but there are a couple of different valve-switching
| protocols, some that latch open and others that accept straight
| TTL at reasonable currents. I need one of those."
|
| That experiment was brought to you by an injector for, I believe,
| a Dodge Caravan, and later, when I needed another, an injector
| for a Ford Mustang. Fuel-injectors are _really_ good valves.
| mr337 wrote:
| Some of the automotive stuff is really great to get started.
| Was working on an agriculture robot and needed a good way to
| detect a level of something. In short a IP65+ hall effect
| sensor that can get wet and dirt no problem.
|
| The solution was a $12 ride sensor from a Cadillac SUV of some
| type. Worked perfect!
| lostlogin wrote:
| I had a friend automating a production line and he needed to
| detect the level of peanut butter in a vat. He settled on an
| ultrasonic device as basically anything else ended up caked
| in peanut butter. It was an impressive setup, all done in
| Arduino.
| TheMagicHorsey wrote:
| I wonder if its practical to DIY your own production line
| automation today with Arduino. Like if I had a simple
| product, could I buy stuff off the shelf and integrate it
| myself in my garage and end up with a little mini-factory?
| Exciting to think about.
| lostlogin wrote:
| The person I was describing runs a food production line
| and has modified various bits of equipment for speed,
| efficiency, safety and ease of use. They have got great
| results. They have no formal training, have no software
| background and basically go to https://www.dfrobot.com
| and get what they need, then hack.
| simcop2387 wrote:
| Probably not impossible, but I think the bigger thing
| will be the time to research the mechanical design of
| whatever you're doing. That and finding reasonably priced
| sensors that will be reliable.
| TaylorAlexander wrote:
| I obsess over this concept. I am a robotics engineer and
| my dream is local manufacturing with small DIY machines.
| But it's a lot of work! When I have a little more time I
| want to teach community robotics classes and build
| machines that makes shoes and hot food and other
| important goods, designed and built as a community. I
| designed a cheap large format laser cutter [1][2] and now
| I am designing shoes that can be made with a 3D printer,
| the laser cutter, a sewing machine, and some basic tools.
| [3]
|
| [1] https://twitter.com/TLAlexander/status/14803321812852
| 12160
|
| [2]
| https://github.com/tlalexander/large_format_laser_cutter
|
| [3] https://twitter.com/TLAlexander/status/14895196927125
| 38113
| matheusmoreira wrote:
| That is so cool. I wish you success.
| [deleted]
| toiletfuneral wrote:
| Made a a pretty sick vacuum tube in high school with clear
| acrylic and put a shrader valve on it so it could be easily
| decompressed with an auto shop ac recharge machine. I won the
| shit out that science fair showing a feather drop like a rock
| theptip wrote:
| At $20k estimated cost, you are getting into territory where the
| TAM of non-medical uses may be higher.
|
| Sports physio / trainers would kill to be able to do regular MRI
| on their athletes. Being able to do pre/post workout imaging, and
| the kind of training programs this level of visibility would
| unlock, are quite exciting.
|
| Assuming you can generalize from brain to whole-body, I think you
| could sell one of these to every major sports team in the
| country, and making it a non-medical device (ie skipping the FDA)
| would let you iterate much faster. A couple more halvings in
| price and this is accessible to every sports physio office and
| gym in the country.
|
| Very cool!
| mrfusion wrote:
| Could this be an alternative to Elon's neural link? Is it
| wearable?
| endymi0n wrote:
| Apart from the potentially massive significance to low-income
| countries and health costs, does someone has a good grasp on the
| applicability of the algorithmical advances towards classic MRI?
|
| My current gut feeling is like: If 0.055 Tesla can create this
| kind of image quality, what could we possibly expect at 1.5 or
| more?
| lostlogin wrote:
| You can expect a lot and you get it. It's truely impressive
| what a bog standard 1.5 or 3T magnet can do and how fast it can
| do it. A standard brain protocol will often include whole brain
| imaging at 0.8mm x 0.8mm x 0.8mm voxel size or thereabouts. It
| takes about 4-5 minutes. A leg angio done from start to finish
| in 20 minutes. This is without more advanced processing, and
| some clever processing is coming into clinical use now. Deep
| Resolve (Siemens) and Compressed Sense/Sensing
| (Philips/Siemens) are what I'm thinking of. Faster scans, or
| more resolution in the same time. It's a good time to be using
| MRI.
|
| Edit: Compressed sense/sensing is not some AI/Machine learning
| thing. It's pretty neat though, a PR video here.
| https://www.siemens-healthineers.com/magnetic-resonance-imag...
| rexreed wrote:
| So you're saying we have sufficient trust in the same sort of NN
| technology that confuses 8's and 0's in OCR text will be used to
| impute image data which might or might not exist? Sure, NN's are
| great at "filling in the gaps" and colorizing pictures based on
| what might be assumed, but when accuracy matters, does this
| approach truly work?
|
| EDIT: I just want to point out that the original subject title of
| the post on HN was "A low-cost and shielding-free ultra-low-field
| brain MRI scanner Using AI" ... and the Using AI part of the post
| title was subsequently removed.
| tshaddox wrote:
| Do you have any data on the reliability of OCR systems used in
| production? I don't have any such data, but given that the USPS
| was using OCR to sort mail over 50 years ago I would be
| surprised if these systems aren't incredibly accurate.
| rexreed wrote:
| From: https://research.aimultiple.com/ocr-technology/
|
| "There are still no OCR tools that work at human level in
| most applications"
|
| and also from my personal experience working with this
| technology every day. There are many more mistakes in OCR
| even with printed material than might be expected.
|
| There is a major problem with Xerox Scanners and the 8's and
| 0's issue I reference.
| isoprophlex wrote:
| See other comments. The nn is used to clear up electromagnetic
| inference as there's no shielding cage. It's not anything lik a
| superresolution approach on the processed voxel data.
| rexreed wrote:
| Ok good clarification as the title of the post seems to imply
| much more than just fixing interference. As always, the
| article subject is the hook that gets you in and then you
| realize it's not as might have been expected.
| ck2 wrote:
| Now build a truck with MRI in the back and drive to where it's
| most needed.
|
| They already do this with DEXA body scans.
|
| Examples: https://bodyandbone.com/mobile-dexa-services
| https://body-comp.com/testing/mobile-dexa/
| https://www.bodyspec.com/
| [deleted]
| ubercore wrote:
| There have been CT scanners put in helicopters as well:
| https://www.auntminnieeurope.com/index.aspx?sec=ser&sub=def&...
| a-dub wrote:
| woah. woah. woah. hold on a second here... are we comfortable
| enough with understanding all of the behavior of deep learning
| models to where we can confidently put them in the pipeline for
| diagnostic clinical imaging?
|
| i'm okay with using them for image analysis, but denoising and
| other image production tasks seems dangerous. how do you know
| what you're looking at is real as opposed to something that just
| looks convincing? (like deep neural nets are famous for
| producing)
| iancmceachern wrote:
| Yes. This is past tense, other companies are already doing
| this, in the clinic.
| lostlogin wrote:
| A link: https://www.siemens-healthineers.com/magnetic-
| resonance-imag...
| fluidcruft wrote:
| Deep learning reconstructions are already marketed/sold in
| high-end commercial scanners.
| axg11 wrote:
| Whether you're comfortable with it or not - it's already
| happened and in production. Look up Subtle Medical and GE AIR
| Recon.
| lostlogin wrote:
| Literally just purchased this - Installed tomorrow:
| https://www.siemens-healthineers.com/magnetic-resonance-
| imag...
| MauranKilom wrote:
| Agreed, but I believe "using AI for inference from sparse
| observations" is unfortunately a thing already.
| lostlogin wrote:
| It's not unfortunate, it improves acquisition times and image
| quality - I use it daily.
| VikingCoder wrote:
| That's not "unfortunate."
|
| Sparse observations save lives. A quicker MR. Less X-Ray
| exposure.
|
| It's totally valid to worry about validation, but to the
| degree you can validate image processing algorithms of any
| kind - AI or otherwise - they absolutely save lives.
| aidenn0 wrote:
| NMRI use microwaves, not x-rays.
| VikingCoder wrote:
| I was talking about MR and CT. Applies to PET, too.
|
| Image processing saves lives.
| lostlogin wrote:
| Yes, and when a quick MRI is available, it can remove the
| need for a CT. Fast brain protocols are now less than 5
| minutes. This makes things practical that weren't before.
| l33tman wrote:
| This project doesn't use AI to improve the image, they use it
| to estimate the EMI noise from the surroundings. So they're not
| "filling in the gaps" in the actual resulting 3D voxel volume
| with fantasy voxels (which I hope will never ever fly in a
| clinical setting).
|
| "To tackle the EMI signals from the external environments and
| internal low-cost electronics during scanning, we developed a
| deep learning driven EMI cancellation scheme"
|
| So it's kind of using deep learning to improve the SnR in the
| RF reception. Of course this could theoretically also lead to
| "fantasy voxels" but due to the nature of MRI decoding, I'm
| willing to guess that bad predictions of the EMI interference
| will not show up as unnoticeable alterations of realistic
| tissue imaging but rather as artefacts all over the volume,
| like you normally see in clinical MRIs that weren't taken 100%
| optimally.
| ortusdux wrote:
| I'm glad that this is the approach that they are taking.
| There have been plenty of issues with fMRI false positives
| due to misconfigured software.
|
| The most famous would probably be the IG Nobel winning study
| that detected brain activity in a store-bought salmon:
|
| https://blogs.scientificamerican.com/scicurious-
| brain/ignobe...
|
| https://www.discovermagazine.com/mind/fmri-gets-slap-in-
| the-...
|
| Later studies called into question the results of between 10%
| and 40% of historic fMRI studies:
|
| https://blogs.warwick.ac.uk/nichols/entry/bibliometrics_of_c.
| ..
|
| https://www.pnas.org/content/113/28/7900
| WalterSear wrote:
| I prefer to think of that study as evidence for life after
| death.
| jacquesm wrote:
| > The most famous would probably be the IG Nobel winning
| study that detected brain activity in a store-bought
| salmon:
|
| A store-bought _dead_ salmon.
|
| I am assuming that most salmons bought in stores are dead
| but that particular detail is rather relevant here.
|
| Also that had me laughing, what a great move.
| robwwilliams wrote:
| Not sure the dead salmon is relevant. That paper is
| focused on false discovery in FUNCTIONAL MRI. Different
| can of fish. Most clinical work is structural MRI.
| jacquesm wrote:
| The chances of finding brain activity in a dead salmon
| are a bit lower than finding it in one that is alive.
| prefrontal wrote:
| Thanks for the kind words. I am the first author of the
| "Neural correlates of interspecies perspective taking in
| the post-mortem Atlantic Salmon: An argument for multiple
| comparisons correction" paper. Happy to take any questions
| here. A link to the original poster:
| http://prefrontal.org/files/posters/Bennett-Salmon-2009.pdf
| nichos44 wrote:
| Those false positives are because fmri runs countless
| statistical tests and the earlier "misconfigured software"
| wasn't running stringent enough multiple comparisons
| corrections. Basically the same issue in the classic "jelly
| bean causes acne" xkcd (https://xkcd.com/882/). The exact
| number depends on voxel size, temporal resolution, and
| experimental condition but is somewhere close to tens of
| thousands of tests.
|
| The "images" that are presented in fMRI studies and that
| contain false positives are representing results of
| statistical tests (t-values, and f-values after correction)
| not the contents of voxels. So the false positive rate of
| an fMRI has very little to do with the accuracy of a
| voxel's content in a structural MRI.
| a-dub wrote:
| the primary innovation is using deep learning to denoise the
| signal and the cost savings derived from being able to use a
| noisier signal.
|
| whether you call it "SnR improvement" or "additive noise
| cancellation", it is undeniably adulteration of the signal.
|
| looking at the supplementary information, it looks like this
| paper was reviewed by mr-physicists. i think it also should
| have been reviewed by ml experts as well.
| petra wrote:
| It's better than nothing. Let's start with those situations,
| and slowly build a database proving or disproving this
| technology.
| jcims wrote:
| >However, MRI accessibility is low and extremely
| inhomogeneous around the world. According to the 2020
| Organisation for Economic Co-operation and Development (OECD)
| statistics, there are approximately 65,000 installations of
| MRI scanners worldwide (~7 per million inhabitants)
|
| Given that my little podunk hospital in the midwest seems to
| have roughly 5x the worldwide average number of MRI machines,
| totally agree.
| lostlogin wrote:
| MRI is also a massive revenue generator. That's a key
| reason they buy them.
| mattkrause wrote:
| Amen!
|
| I have seen an alarming number of talks where someone proposes
| to algorithmically add Gado contrast or turn a T1 into a T2
| image. In a few very specific contexts, this makes sense (e.g.,
| aligning a T1 taken in one session with a T2 taken in another).
| Otherwise though, it seems dangerous to mistake a "real" image
| with the expected image given another one.
| lostlogin wrote:
| If reducing gadolinium dose is the aim, a more prompt
| following of the literature, radiologist request (rather than
| surgeon demand) and weight based dosing would drastically
| reduce dosage. A moaning radiographer, what a surprise!
| phkahler wrote:
| I'm kind of thinking the opposite. Image analysis is where you
| don't want AI. Noise removal is further upstream (I'm assuming)
| and if it fails wouldn't it cause significant artifacts (blur
| for example) in the images?
|
| It would be helpful to see results with and without this
| correction, or even with varying degrees of it.
| VikingCoder wrote:
| That's a valid risk.
|
| You're asking a cost-benefit question.
|
| The cost of an invalid diagnosis is indeed high.
|
| The cost of no diagnosis at all is also high.
|
| This device will not replace the MR at your local hospital. It
| will be the first MR device in hospitals that have never had
| one before.
| lostlogin wrote:
| Veterinary MRI may be another application.
| VikingCoder wrote:
| Good point. Cargo inspection? Luggage inspection? I dunno.
| lostlogin wrote:
| There are a lot of applications that are surprising. I've
| scanned for salmon farmers (is that the term?) who want
| to check they are breeding good fish and are looking at
| spine alignment.
|
| I've scanned logs for forestry managers who want to look
| at something in their trees.
|
| I've scanned old hearts that have been sitting in
| formalin for decades.
|
| All are probably better at higher field strength but
| maybe some of that can be compensated for by scanning for
| longer? A log isn't going to move, and a dead fish scan
| is likely only limited by the time it takes for it to
| rot.
|
| I'd be scared of scanning unknown things, it might be a
| low field MRI, but it's still a big magnet.
| scratcheee wrote:
| Exactly my thoughts too. I'm fine with a simple noise-removal
| pass, but if the AI is context-aware, what's to stop it saying
| "hmm, this brain would look more like a normal brain if I
| remove these tumors". Obviously, they'll test for that, but
| that only handles common cases they concider, it's always going
| to be a risk for more unusual sceanrios, and the danger with
| altering the data is that anyone looking at the results wont
| have a way to tell how dubious that data is.
|
| Reminds me of
| https://en.wikipedia.org/wiki/Xerox#Character_substitution_b...
| which was _so much_ worse than the equivilent OCR bug because
| it occured at the image level, where everyone expects errors to
| to produce noise, not contextly sensible and sharp _but wrong_
| characters.
|
| EDIT: based on other comments below, this is thankfully not the
| case, the AI just understands noise, it doesn't try to "fill in
| the blanks" based on how brains are supposed to look.
| xattt wrote:
| Therein lies the dilemma of this technology: would a scanner
| that might sometimes substitute information be better than no
| scanner at all?
| robwwilliams wrote:
| The ML denoising is within-sample across voxels---or so I
| presume from similar work in small animal MRI. And you can
| always have the "with" and "without". I do not see any
| problem if a radiologist is in the review process.
| jart wrote:
| How do you know? They're both based on neural networks. JBIG2
| was also responsible for the Pegasus FORCEDENTRY thing.
| robertlagrant wrote:
| > a simple noise-removal pass
|
| Even that is inventing data, no?
| scratcheee wrote:
| Yes, but context is key.
|
| Denoising can on average improve the result, but sometimes
| it will be wrong.
|
| Spotting when it goes wrong is potentially a difficult
| task, but generally the difficulty scales pretty clearly
| with the difficulty of understanding the original image
| anyway. If you can't spot when a denoising filter has
| screwed up, chances are you wouldn't have spotted anything
| interesting in the original image anyway.
|
| But once an AI is context-aware things get way more
| complicated - it will try very hard to produce an image
| that doesn't _look_ wrong. Even if it goes wrong, it can go
| wrong and still succeed in managing to make an image that
| looks correct, it just no longer matches the real brain
| that was scanned. Perhaps it decided a tumor was just a
| smudge on the lense, and invented some brain to go behind
| it. An operator expecting to see brain and seeing brain
| wont think anything of it. When the patient dies, they may
| look back and say "wow, that tumor didn't exist at all just
| 3 days before! that should be impossible!".
|
| tldr: Having an ai that might make mistakes is one thing,
| having an ai that can just invent exactly the data everyone
| is expecting to see is dangerous.
| tshaddox wrote:
| Hopefully the system would be trained to accurately convey
| relevant medical information rather than to generate an image
| of a brain that looks normal.
| alehackp19 wrote:
| walterbell wrote:
| Code/data for replication: https://github.com/bispmri/Ultra-low-
| field-MRI-Scanner
| phkahler wrote:
| Some of the code is Matlab. I wonder if GNU octave is
| sufficient to run it. That would be a big savings for studying
| this.
| keewee7 wrote:
| I am surprised that there isn't open source alternatives to
| Simulink, Stateflow etc.
|
| One reason Matlab is popular in academia and industry is
| because someone who don't know C/C++ (mechanical engineers
| etc.) can use something like Simulink to program real-time
| systems on microcontrollers and FPGAs.
| neuronexmachina wrote:
| The only Matlab file seems to just be be ~30 lines of code
| for reading HDF5 files and plotting some results, nothing too
| complicated or critical: https://github.com/bispmri/Ultra-
| low-field-MRI-Scanner/blob/...
|
| It looks like the bulk of the code for training the EMI
| elimination model is is pretty straightforward PyTorch.
| devwastaken wrote:
| How does this fare against patents? Isn't pretty much everything
| to do with the actual implementation of an MRI patented and
| copyrighted in some way to prevent anyone else from entering the
| game?
| ska wrote:
| The basic patents all expired ages ago. There are details
| patented by everyone, but there is a lot of FTO.
|
| The real barrier to entry is cost. Building out a permanent
| magnet system like this is likely an order or two cheaper
| though.
| aidenn0 wrote:
| The very first NMRI images were published in the early 70s, so
| at least some of what is required must be public domain now.
| The original diffusion and perfusion patents are both from the
| 80s, so should also be expired I think?
|
| That being said it's very hard to make any even slightly novel
| machine (MRI or otherwise) that isn't so close to an existing
| patent that a judge would dismiss a suit out of hand.
| egocodedinsol wrote:
| "There are approximately seven scanners per million inhabitants
| and over 90% are concentrated in high-income countries. We
| describe an ultra-low-field brain MRI scanner that operates using
| a standard AC power outlet and is low cost to build."
|
| This is fantastic. What a sentence to get to write.
| cute_boi wrote:
| Yea, the way they turned the bleak situation into something
| sanguine is fascinating. I still remember how expensive is MRI.
| I used to earn like $150 usd and the cost was around $200 usd.
| I hope such inequality shall perish in the future, so people
| can at least get proper treatment.
| asiachick wrote:
| I'm curious what makes them expensive. In Japan they are
| basically free (covered by national insurance for which the
| price is low). I believe at one point Japan had the most MRI
| machines per capita. I think the government just decided they
| were worth while and got a bunch where as in the USA they
| were seen as a money source and they generally charge $1k to
| $10k ?!?!?!
|
| I'd love for the expensive ones to be disrupted. The dream is
| we get some attachment for our smart phones and turn them
| into Tricorders.
| morcheeba wrote:
| I worked for a medical company that did RF tumor ablation.
| In Japan we sold a machine that cooked small tumors as an
| out-patient procedure, because their easy MRIs would spot
| them early. In the US, we sell more complicated machines
| that work on bigger tumors because we find them later here
| - when they get too big, you have to be very careful not to
| damage surrounding tissue.
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