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34C3 - Low Cost Non-Invasive Biomedical Imaging

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    Music
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    Herald Angel: And now we come to the talk
    entitled low-cost non-invasive biomedical
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    imaging. Current medical imaging has
    problems: it is expensive, it is large,
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    rarely preventively used and maybe you've
    heard of the story of a fMRI - this is the
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    magnet resonance tomography - they put in
    a dead Salmon and they can get a signal
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    from brain activity from it. There's also
    lots of problems in the software as well.
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    A little story, maybe you look it up. And
    how this whole mess can be solved with the
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    technique called Open Electrical Impedance
    Tomography - this will tell us Jean
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    Rintoul. Give a big round of applause for
    Jean.
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    applause
    Jean Rintoul: Thank you.
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    Hello everyone. Today I
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    will be talking about an open source route
    for biomedical imaging using a technique
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    that's in R&D called Electrical Impedance
    Tomography. Not many people have heard of
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    it, which is why it seems like it's
    important to mention. First of all, I'll
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    just give you the vision of what it would
    be like if everybody had access to cheap
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    biomedical imaging. Right now you only get
    imaged when something's gone wrong. And,
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    moreover, you only actually get to use
    these tools when something has gone wrong
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    in a first world country when you're lucky
    enough to be close to a hospital and have
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    access to these technologies. That's a
    very limited number of people. What's even
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    worse about it: is it's hard to hack! So,
    if you wanted to improve this technology
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    yourself - medical physics is an amazing
    field - but it would be very hard to do so
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    because you don't have a three million
    dollar MRI scanner sitting in your garage.
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    Maybe you do, that's good for you, just
    not many of us do. If we did have cheap
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    biomedical imaging we could do things like
    do preventive scans so you would wake up
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    in the morning you'd like, take a shower,
    the device would be quietly imaging your
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    body, would warn you if the slightest
    little thing when went wrong. You'd do
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    machine learning over it, it'd be
    wonderful wonderful for health care. So,
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    that's the vision of what biomedical
    imaging could be. And the other point is
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    sometimes we move forward faster when we
    share the information. I worked in defense
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    for a brief period and people didn't
    really share information between each
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    other, and I think that inhibited science
    from moving forward. So, sharing is
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    caring.
    So today I'm going to go through a few
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    different things. I'm going to go through
    the current biomedical imaging
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    technologies. I'll give you an
    introduction to Electrical Impedance
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    Tomography. I'll go through the open
    source Electrical Impedance Tomography
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    Project. Then I'll go through some
    applications that we could apply it to.
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    And then I'll suggest a few different next
    steps that we can go into because by no
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    means is it finished. Right now we have
    four different main existing imaging
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    modalities. Your MRI scanner, which is a
    wonderful tool, it's huge, very expensive.
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    The most commonly used imaging is actually
    CAT scanner which sends our x-rays through
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    your body which is ionizing radiation,
    which is bad for you because it causes
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    cancer in the long run if you get too many
    of those scans and it's actually the first
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    first scan that you'll get when you go
    into the emergency room. It's the most
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    commonly used. And as we all know we've
    got those grainy images that come from the
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    ultrasound of fetuses, wonderful tool
    except for the scattering due to the sound
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    gets scattered when you have different
    density materials next to each other. And
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    not exactly an imaging modality but a very
    important diagnostic technique is EEG.
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    So you might ask, how do we classify these
    right now? we have 3 main types of
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    resolution. Spatial, contrast, and time.
    Spatial resolution is, basically, what
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    space you can determine 2 different
    objects from each other. Contrast
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    resolution is soft tissue or subtle
    differences in tissues. And time
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    resolution, as it sounds, is how things
    change over time and how quickly you can
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    do these images together. Your CAT scan,
    your basic machine in a hospital,
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    costs 1 to 2.5 million dollars.
    You probably didn't get one for Christmas
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    to play around with. Oh well. It's also
    got this ionizing radiation, you've got
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    a lot of maintenance, and
    dedicated technicians.
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    An MRI, say, your average 3 Tesla magnet
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    with its own helium quenching chamber
    no less, as well as dedicated technicians
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    and experts who can actually read
    the images. Again $3,000,000. An amazing
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    and beautiful technology, but really
    expensive. Amazing spatial resolution, the
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    best. When it does something at this very
    high spatial resolution, it actually takes
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    4 minutes and 16 seconds. Which is a
    really long time to take to do this
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    wonderful spatial resolution image.
    Ultrasound, it's a bit grainy due to
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    scattering. On average it costs about
    1$115k, not too bad. It's a pretty minimal
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    health risk. EEG. EEG doesn't do any image
    reconstruction. In fact it does very
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    little in many ways. But it is still very
    useful. Your average medical grade by EEG
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    system is $40k. You might also know of
    some open source EEG projects which are
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    pretty cool. So just a note on the
    radiation of CAT-scans. It's actually the
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    biggest contributing cause of radiation in
    the United States. So here I just put
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    those biomedical imaging modalities onto a
    graph so that you can kind of think of
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    them in terms of spatial resolution and
    time resolution, and where they fall in
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    the picture of common things that go wrong
    with people. Like, X-rays or CAT scans are
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    great for for looking at bone and bone
    breaks; pulmonary edema, that's water on
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    the lung ,tuberculosis, huge in third-
    world countries, massive problem. You
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    don't actually need super high spatial
    resolution to be able to detect it. And
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    it's important to sort of understand what
    you can do at different spatial and time
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    resolutions. Under like, the optimal goal
    of all of this, I put non-invasive
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    electrophysiology. What that is, is high
    spatial resolution and high time
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    resolution. That's where you can measure
    ion activation, or basically what cells
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    are doing when they communicate with each
    other, which is right now only done in an
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    invasive manner.
    Today I'm gonna talk about this new
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    technique called Electrical Impedance
    Tomography and describe where it will fit
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    in amongst what already exists. So what is
    it. Okay yeah basically you send AC
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    currents through the body, say a 50
    kilohertz current. And that will take
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    different routes based on what tissue
    there is. So it might go around some cells
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    and straight through others. And that's
    really important because differentiating,
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    say, fat from muscle is one thing that you
    could do. But you can go further and
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    differentiate, say, tumors from healthy
    tissue. Because tumors have different
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    impedance spectra to the healthy tissue.
    So as you can see, that would be very
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    useful to do. This set up here is a called
    a phantom. What it is, it's like a
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    simulated human body. You get some
    saltwater - the body is 80% water as you
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    might know -you get some meat or
    vegetables. You put it inside and then you
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    use that to image. So we have current
    flowing through all these different
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    directions and we recreate an image. Right
    now it's used for lung volume
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    measurements. This is a baby with an EIT
    setup. Muscle and fat mass, there's a
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    paper on gestural recognition that just
    came out this year, you can look at
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    bladder and stomach fullness. There's some
    research papers on breast and kidney
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    cancer detection. There's another research
    paper on hemorrhage detection for stroke.
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    You can also look at the ... there's more
    R&D on the depth of anesthesia in in
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    surgery as well, which would be another
    interesting use for it. So all of these
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    are sort of in the works and you might
    ask, "Great, that sounds amazing, why
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    isn't everybody using it already?" Well
    yeah it's really an R&D technique right
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    now and it has a big problem: its spatial
    resolution seems pretty limited. So it's
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    limited by the number of electrodes. But I
    will discuss some potential ways to get
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    around that. As we go, it might not ever
    get to the spatial resolution of MRI.
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    But maybe we don't need it to to be
    useful. Because it's so compact. It's so
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    cheap, nothing about it is expensive. It's
    got better source localization than EEG.
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    It does not ionize,
    it's not harmful to human tissue. It's
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    also got great time resolution, so it has
    advantages and disadvantages. I'll just
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    remind you of what the first MRI scan
    looked like at this point in time. As you
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    can see it looks pretty crappy in 1977.
    And now it looks pretty awesome. That's a
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    slice of my head by the way in a 3 Tesla
    MRI scanner. This is what early EIT looks
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    like. That's with 16 electrodes only. What
    will it look like in a few years time I
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    don't know. I hope that MRI gives you a
    pathway that it will take take too.
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    Now I'll introduce you to the OpenEIT
    project. The OpenEIT project is obviously
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    open source. It has a PCB design done in
    Eagle CAD. It has firmware written in C.
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    It has a Python dashboard that lets you
    see the reconstruction in real time. It
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    also has a reconstruction algorithm which
    I'll go into. And you can get it from
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    github right there. So how does it
    reconstruct an image? OpenEIT right now
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    has 8 electrodes and what you do is, you
    send this 50 kHz current through every
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    combination of those 8 electrodes and you
    get a different impedance value for each
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    of those measurements. On the left you can
    see basically what you're doing. You know where the
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    electrodes are positioned and you get one
    value going horizontally. You add it to
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    another value coming from another
    direction. And again, you can sort of see
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    it's getting a low resolution image as it
    goes around adding those values together.
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    If you use many, many views you bring the
    image back. This is the radon transform,
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    that's what it's called, and you
    basically just send lots of current
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    through these different slightly different
    angles and you build up something called a
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    sinogram which is over there. And then you
    invert it to get the image back. I used
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    OpenCV which is a really common image
    processing library to do this. You can
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    just do it with a regular image yourself
    and try it out. But what I did is exactly
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    the same as what you do with a regular
    image, except I use current to be the
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    input data. So this is the PCB design
    in Eagle. Basically it has a
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    few different features. A connector for
    your 8 electrodes. It's running an ARM
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    Cortex M3, which is quite nice. It has a
    dedicated DFT engine for doing your direct
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    Fourier transform in real, time which is
    also quite nice. A JTAG debugger to easily
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    reprogram it. It's got coin cell or
    external battery options. It has UART to
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    get the serial data off. And you can also
    flip it to Bluetooth mode and get the data
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    off by Bluetooth if you felt like going
    Wireless.
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    At this point you might be asking "Is this
    safe for me to play around with?", which
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    is a really great question because the
    answer is actually "Yeah! it is". There's
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    some guidelines called the IEC60601-1
    guidelines for safer use in humans. And
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    basically which says it should be, and
    openEIT is less than 10 micro amps which
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    is great because that's well within their
    guidelines. If you want to compare it to
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    other things that are completely legal,
    say I don't know if you've seen there's
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    like late-night TV ads for those abs
    stimulators that stimulate your muscles,
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    there are about 15 to 20 milliamps just
    for reference and as a scale to look at
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    the 10 micro amps. So some of you might
    have used them already and that's hugely
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    more current than what we're putting
    through to image the body here. This is
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    what the dashboard looks like. It does the
    reconstruction. You can connect to serial
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    at baseline. You can obviously adjust
    sliders to look at the area that you want
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    to look at. You can read from a file and
    fiddle around however you would like to.
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    This is what it looks like when you
    reconstruct something. I have a phantom up
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    there which is a part of water with a cup
    in it. I moved the cup around anti-
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    clockwise so you can see in each of the
    pictures I move it around a little bit
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    more. And you can see the reconstruction
    there with me moving the cup around again.
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    This might not be wow-ing you with the
    resolution, with only 8 electrodes. It's a
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    proof of concept but that's okay. Let's
    see if we can make this I make this go.
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    Here's a real-time video demonstration of
    it. Here's me with a shot glass. I'm
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    moving around anti-clockwise. Hopefully
    you can see on the left the image being
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    reconstructed in real time. And there we
    go, move to the bottom. You can see it
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    over there and again up to the top. you
    can see it over there. So that's a basic
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    proof of principle version of it running.
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    So the first MRI scan of human
    lungs wasn't that amazing.
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    Early EIT scan wasn't either.
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    applause
    Something else that you can use it
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    that for is differentiating objects.
    Multi-frequency. This is what they're
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    doing the breast cancer and kidney cancer
    scans on. Basically you send different
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    frequencies through these times, called
    multi-frequency Electrical Impedance
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    Tomography and you build up a spectrum.
    Here I've got an apple, a pear oh no a
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    sweet potato and and some water. And I've
    sent through these different frequencies
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    and I get these different spectrums.
    They're different, you can see that
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    they're different. They're quite obviously
    different but yeah you can also just
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    simply classify. And on the left you can
    see where the water is, the apple is, the
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    sweet potato is. Or, the sweet potato and
    the apple a little bit harder that one.
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    But that's basically what you do when you
    detect cancer. So that's what I did. But
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    maybe we should look at the other papers
    and see what they did because they did
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    better than me. So there's this guy called
    Aristovich, 2014 he published spatial and
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    temporal resolution, and using this
    technique 200 micro meters less than 2
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    milliseconds which covers most of the
    applications that I listed on that graph
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    at the start of the talk. The downside
    here is that it was an intracranial array,
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    so it was under the skull. So very dense
    electrodes, a lot more electrodes. I only
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    used 8 he used like 256 so you can see
    that it can be, like, the potential is
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    there.
    So how should we use it first? what's a
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    nice low hanging through fruit? What about
    medical imaging in the developing world
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    where I believe 4 billion people don't
    have access to medical imaging. No MRI, no
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    CAT scans. Why is the EIT good for that?
    It's cheap to mass-produce, super
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    portable, super low power. So that would
    be a great place to start. What could we
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    do first? I'm going to go back to this
    image again and have a look. Tuberculosis
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    affects a lot of people in the developing
    world and you don't need amazing spatial
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    resolution to detect it. That would be a
    good one. Or what about a pulmonary edema?
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    Pulmonary edema is water on the lung. It's
    actually already used for that. You can
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    quite easily see the different volume
    present, or the different conductivity
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    maps it's called, of a working lung and a
    not so working lung right there.
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    Next steps. So what should we do to make
    this technique better? What should we do
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    for OpenEIT to make it better? If you want
    to innovate again, that's the github
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    project. Just go ahead. Oh that's an
    avocado, it has a seat in the middle. Who
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    knew? I do. So I see the two main routes forward
    as: One would be this low-cost biomedical
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    imaging for the developing world. You
    could just stick with the static imaging
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    reconstruction because why not. you'd need
    a few more electrodes than it currently
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    has. One of the main problems with the
    technique is how you stick it to the skin.
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    So my suggestion for that is why don't you
    just use a water bath and stick the body
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    part of interest in a body of water,
    because water gets rid of a lot of the,
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    it's called the contact impedance problem.
    Or, on the kind of exciting science front,
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    you've got the advancing neuroscience
    option. Which would be measuring both high
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    spatial resolution and high time
    resolution. So that's the non-invasive
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    electrophysiology solution. Or, and that
    would be super awesome, there's a couple
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    of ways forward to do that and I'm going
    to sort of discuss each of those.
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    So roughly there's physical configuration
    improvements that could be done. There's
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    things that you can do to improve the
    spatial resolution. There's things you can
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    do to improve the time resolution. And
    this is interesting tack on at the end
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    that I thought I'd mentioned, which is
    'write' functionality. So we're using very
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    small currents to read an image. What if
    we pumped the current up a little before
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    you know it you're writing. I think not
    invasive deep brain stimulation in a
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    focused way, that would be very very cool.
    So, contact impedance. Major problem right
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    now, there is a well-known solution I
    haven't done it yet you do this thing
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    called differential referencing, common
    mode rejection should be done I haven't
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    done it that's the next step. That means
    that it will work when you just attach it
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    with electrodes on the body. What happens
    is, electrodes have a like some
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    capacitance and different amounts which
    kind of interfere with the the measurement
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    that you want to make which you want to be
    very accurate and just of your body. You
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    don't want to include the electrode
    information in there that's changing.
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    There's a way to remove that that's well
    known already. Another physical
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    configuration improvements: just increase
    the number of electrodes. Wonderful, now
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    you've just improved the resolution. Or
    the placing the part in water. Another set
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    of next steps would be on the mathematical
    side. I mentioned that I use linear back
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    projection which is a wonderful technique,
    that's how they do CAT scans. With X-rays
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    that's exactly what they do.
    However, it makes some appalling
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    assumptions, like parent moves and
    straight lines. That is not true. What you
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    should do is get a finite element model
    and solve Maxwell's equations because
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    current bends around objects. Actually it
    works in three dimensions too which might
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    not be all that surprising but it needs to
    be solved for those three dimensions which
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    is why you just need to solve
    Maxwell's equations and
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    create a finite element model.
    And there's a quite a bit of work on
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    mathematical solutions that get higher
    resolution.
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    That's another improvement area. And now
    as I mentioned this awesome new technique.
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    Which, actualy there's a paper on
    this year called
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    magneto-acoustic electical tomography.
    You might remember
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    the FBI rule from high school.
    When you have a current flowing,
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    perpendicular to that there will be a
    force. Now that force, say it's vibrating
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    with 50 kilohertz. that's the AC signal
    that you're sending through. Now you have
  • 23:07 - 23:11
    a vibrating compression wave. That's
    sound. You can pick that up with a little
  • 23:11 - 23:20
    piezoelectric element. And that's actually
    a focus of work. From that you can get
  • 23:20 - 23:27
    really good edge information, because as I
    mentioned earlier, sound scatters at
  • 23:27 - 23:31
    edges. So you would also get the
    electrical impedance tomography
  • 23:31 - 23:39
    information for the tissue sensitivity.
    Why not combine those results together and
  • 23:39 - 23:43
    you would have a better tool. It currently
    gets lesser resolution in the middle
  • 23:43 - 23:50
    simply from how you every combination of
    electrodes just ends up having a less
  • 23:50 - 23:57
    dense number in the middle. You can also
    do something as simple as increasing the
  • 23:57 - 24:02
    power that you send through if you're game
    to do that. This is a kind of gory
  • 24:02 - 24:08
    picture. Right now epileptics, if they're
    really troubled by their problem, which
  • 24:08 - 24:13
    they are often, they go into a hospital
    have their brains opened up and they
  • 24:13 - 24:19
    stick this array on their head through
    their skull. And they leave it open
  • 24:19 - 24:24
    for a week. And they try to induce
    seizures through sleep deprivation.
  • 24:24 - 24:30
    And then they measure the activation
    potentials that way to locate the foci or
  • 24:30 - 24:36
    where they going to do surgery to stop you
    from having seizures. But it would be much
  • 24:36 - 24:40
    better and nicer if you could do it not
    invasively and you probably can if you
  • 24:40 - 24:44
    improve the time resolution of EIT.
    there's nothing stopping you from doing
  • 24:44 - 24:50
    that by the way. You just have to, like,
    it's just a next step really.
  • 24:50 - 24:57
    And then I'll also mention write-
    functionality. So there was a paper that
  • 24:57 - 25:03
    came out halfway through this year by a
    guy called Neil Grossman (?) and what he
  • 25:03 - 25:09
    did is, he showed that you can stimulate
    neurons by sending current through the
  • 25:09 - 25:19
    skull and in a focused way. Now why that's
    interesting is, you can non-invasively
  • 25:19 - 25:23
    stimulate neurons. So that's the write-
    functionality. It's unknown what
  • 25:23 - 25:28
    resolution is or how well you could
    control the the focal point here. But it
  • 25:28 - 25:34
    works in the principle of beat frequencies
    so he sent through two kilohertz and 2.05
  • 25:34 - 25:42
    kilohertz and basically had a beat
    frequency of 10 Hertz arise from that and
  • 25:42 - 25:50
    basically stimulated neurons in this area
    that he can control via an x- and y-axis
  • 25:50 - 26:00
    which is very impressive. Leaves a lot of
    questions open. Those are some possible
  • 26:00 - 26:06
    next steps that it could go in. Obviously
    I think this is interesting. I hope that
  • 26:06 - 26:11
    you do too. I'd love it if you would want
    to sign up to a mailing list I'll give a
  • 26:11 - 26:17
    link on the next page. If you want to
    collaborate email me. If you know any
  • 26:17 - 26:22
    funding bodies that might be interested in
    the developing medical imaging for
  • 26:22 - 26:26
    the third world I'd love to be put in
    contact. If you wanted a kit and, if there
  • 26:26 - 26:30
    were enough people that wanted a kit,
    probably of the next version which would
  • 26:30 - 26:36
    have 32 electrodes sign up to the mailing
    list, talk to me. Thanks.
  • 26:36 - 26:47
    applause
    Rintoul: Thank you
  • 26:47 - 26:50
    applause Herald Angel: Thank you
    very much. We have a little bit
  • 26:50 - 26:58
    time for Q&A. And please if you have to
    leave the room make it in a very quiet
  • 26:58 - 27:06
    way. So is there ... there are some
    questions I've seen microphone 4 first.
  • 27:06 - 27:09
    Please go ahead.
    Audience member: So, a great thing
  • 27:09 - 27:16
    thinking about developing countries and
    getting them medical tech. But at the very
  • 27:16 - 27:21
    first beginning you said imagine a world
    where this imaging would be all available
  • 27:21 - 27:27
    like every day and it creeped me out a
    little bit. Do you really think that it's
  • 27:27 - 27:34
    a good idea to go in the shower in the
    morning and have your I don't know your
  • 27:34 - 27:40
    bathtub telling you that there is a small
    mass inside your lungs.
  • 27:40 - 27:47
    Rintoul: That's a good question. Basically
    the question was: There's a privacy
  • 27:47 - 27:52
    concern with looking inside your body. It
    doesn't sound that great to some people.
  • 27:52 - 27:56
    To those people I would say you should
    turn off I know that sounds a little
  • 27:56 - 28:05
    harsh. But please just turn it off, don't
    use it. And with all scientific movements
  • 28:05 - 28:12
    forward comes great risk, I also say. And
    it can be used for good or evil and it's
  • 28:12 - 28:18
    up to us as a society how we want to
    choose to use it. And how we structure
  • 28:18 - 28:25
    ourselves and potentially motivate and
    incentivize corporations to use it in a
  • 28:25 - 28:32
    responsible way. Part of making this open
    is I hope that, basically if people have
  • 28:32 - 28:36
    access to it you can choose for yourself
    how you'd want to use it.
  • 28:36 - 28:41
    Herald Angel: And next question would be
    from the Signal Angel please.
  • 28:41 - 28:45
    Signal Angel: Yes I have a couple of
    questions from the internet. First of all,
  • 28:45 - 28:51
    what type of AC frequencies in use? the
    asker assumes sinusoidal but he wonders if
  • 28:51 - 28:55
    you also tried square wave, triangular and
    other shapes.
  • 28:55 - 29:00
    Rintoul: That's also a really interesting
    question. It's about what kinds of waves
  • 29:00 - 29:09
    are used, what kinds of AC signals.
    Typically it's done with AC sine waves
  • 29:09 - 29:14
    ranging all over the place, depending on
    what application you want to use up for. I
  • 29:14 - 29:20
    mentioned multi frequency EIT for cancer
    detection. That uses a lot of different
  • 29:20 - 29:26
    frequencies so if you wanted to use other
    waveforms I think that would be really
  • 29:26 - 29:33
    interesting. Nobody's tried, you can, that
    should be done.
  • 29:33 - 29:39
    Herald: So since there's a big queue on
    microphone 3 I would go there please.
  • 29:39 - 29:45
    Audience member: Yes I have a technical
    question. Assuming that you won't use this
  • 29:45 - 29:51
    techniques on humans or organic matter at
    all and what are the limitations for the
  • 29:51 - 29:56
    resolution. The spatial resolution. And is
    there a possibility to reduce the spatial
  • 29:56 - 29:59
    resolution.
    Rintoul: You mean increase the spatial
  • 29:59 - 30:06
    resolution or reduce it?
    Audience member: Reduce the voxel size
  • 30:06 - 30:12
    Rintoul: So increase the spatial
    resolution. Yes absolutely. So I was
  • 30:12 - 30:16
    trying to go through a few of the next
    steps that could get to that. One of them
  • 30:16 - 30:21
    is magneto-acousto electrical tomography
    because you get two different types of
  • 30:21 - 30:28
    information which you could put together
    to form a higher resolution image. So
  • 30:28 - 30:33
    that's one way and if you didn't need to
    worry about human safety I recommend you
  • 30:33 - 30:39
    just turn the power up, that will also
    work.
  • 30:39 - 30:46
    Herald: Okay I think we go back to the
    signal angel for one short one please.
  • 30:46 - 30:50
    Signal Angel: Yes I have another question
    from the internet. from a doctor this
  • 30:50 - 30:54
    time. He wonders if there are any clinical
    studies that compare pulmonary edema
  • 30:54 - 31:00
    diagnostics with EIT to ultrasound and why
    don't we just work on cheap ultrasound
  • 31:00 - 31:03
    instead.
    Rintoul: That's a good question. People
  • 31:03 - 31:08
    are working on cheap ultrasounds.
    Ultrasound gives different information to
  • 31:08 - 31:14
    EIT. It has a problem of the sound
    scattering. So it's a different type of
  • 31:14 - 31:21
    information which has different pros and
    cons. And and I think people should make
  • 31:21 - 31:27
    cheap ultrasound. And I would like to see
    the hybrid modality come together. You can
  • 31:27 - 31:32
    get really good tissue distinction with
    EIT so there's pros and cons.
  • 31:32 - 31:37
    Herald: Okay then, microphone 2 please.
    Audience member: You had a really good
  • 31:37 - 31:45
    talk my question so far you always need
    direct contact to the electrode, right? So
  • 31:45 - 31:51
    it has to be direct contact or in water.
    Is there way to detect or measure the
  • 31:51 - 31:57
    signal without direct contact? So maybe in
    if the if the object is in air or any
  • 31:57 - 32:01
    other gas?
    Rintoul: Right. I wish there was. No is
  • 32:01 - 32:08
    the short answer. Unless ...
    Audience member: Any research on making it
  • 32:08 - 32:11
    happen?
    Rintoul: Well yeah you can you can use
  • 32:11 - 32:20
    X-rays. They work wonderfully to to go
    through the air. But if you use them I
  • 32:20 - 32:24
    mean you do increase your chance of cancer
    so don't use them all the time on
  • 32:24 - 32:29
    yourself. Again CAT scanners are a little
    bit expensive.
  • 32:29 - 32:36
    Herald: Thank you and I think we have time
    for one more from microphone 3
  • 32:36 - 32:42
    Audience member: My question would be
    what, so maybe I've missed it, but what's
  • 32:42 - 32:47
    the order of magnitude for cost so would
    this be feasible at like a hackerspace for
  • 32:47 - 32:54
    this to implement. And does the industry
    see the possibility to make money.
  • 32:54 - 33:01
    Rintoul: Yes a lot of those sort of these
    early like R&D papers yeah they should be
  • 33:01 - 33:07
    applied and you could make money with it
    absolutely. And there's no component in
  • 33:07 - 33:15
    there that costs more than a couple of
    cents. I suppose a cortex m3 like costs a
  • 33:15 - 33:20
    couple of dollars. And I mean I don't know
    what your budget is but yes you I think
  • 33:20 - 33:24
    you could do this in a hackerspace without
    any problems. There's nothing stopping
  • 33:24 - 33:30
    anyone from doing this and as we know
    microcontrollers are becoming cheaper and
  • 33:30 - 33:36
    cheaper. So why not.
    Herald: I don't get Hasty's signs from the
  • 33:36 - 33:40
    sideline so I think I can take another
    question from 2 please.
  • 33:40 - 33:47
    Audience member: So far you have showed us
    images of 2d planes. What about volumes
  • 33:47 - 33:52
    Rintoul: Yes so there's work on solving
    for volumes using finite element models
  • 33:52 - 34:03
    and solving Maxwell's equations. Basically
    I just did the shortest route to reach
  • 34:03 - 34:08
    image reconstruction that was available
    which was linear back projection which is
  • 34:08 - 34:12
    typically done in a 2d plane. So
    absolutely, you can do it in three
  • 34:12 - 34:16
    dimensions.
    Herald: So I'm very sorry we are out of
  • 34:16 - 34:24
    time the queue back there you can have the
    chance to chat with our speaker just right
  • 34:24 - 34:32
    now. The next talk coming up is in about
    15 minutes and it's I think also in
  • 34:32 - 34:37
    English. See you then and a big round of
    applause for our speaker, excuse me.
  • 34:37 - 34:42
    applause
  • 34:42 - 34:48
    music
  • 34:48 - 35:04
    subtitles created by c3subtitles.de
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Title:
34C3 - Low Cost Non-Invasive Biomedical Imaging
Description:

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Video Language:
English
Duration:
35:04

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