we are big believers in the fact that the Bitcoin blockchain in Bitcoin SV can support all over the world's data so to find out more go to be SV hackathon dotnet and that is one of the great initiatives from Bitcoin Association in addition we have a developer conference coming up July 18th and 19th that we're partnering with we are developers on that will be two days with a lot of information content and advice from the end chain team as well as many companies across the world to help you learn how to build on Bitcoin SV you can register


on the we're developers comm site as well as find out more information at be SV dev con dot net that's July 18th and 19th so it's coming up soon and it's free to register so we hope lots of you take advantage of that opportunity to learn more about Bitcoin SV and that is those are just some of the interesting initiatives we have Bitcoin Association is the global industry organization that advances the business of Bitcoin SD if you want to get involved and learn more about what we're doing visit our website at Bitcoin Association dotnet as an

Bitcoin SV:  The Massively Scaled Blockchain to Meet Developer Needs—Jimmy Nguyen & Steve Shadders


individual developer you can apply to become an Fillie 'it of the association our memberships are really focused on businesses but if you're not involved with a business that is a member become an affiliate of our association and sign up and get lots information about what we're doing in Bitcoin s deal and we're really excited to bring Bitcoin SP to the world we think it is going to be the global blockchain for enterprises and developers with big power as Steve said big blocks big transactions big script and big capabilities for everyone with


that I think we have some time for questions so Steve one of the kitchens is is there a specific language you have to use for the DEF CON a specific language you have to use well no I mean the DEF CON itself is more of a more of a learning event I suppose but there'll be a number of tools which we'll be showing off some of which are actually languages themselves so the aim of Bitcoin is not to be language specific for example s script is one particular language that you can use for scripting but of course you don't need to actually


get down into the weeds of Bitcoin scripts to make use of a Bitcoin there are plenty of tool sets available in all sorts of languages the JavaScript go - and rats Darla any anything you can imagine probably there are tools available so use whatever language you're comfortable with problem with the fluctuating price for B or C or B SVR other other blockchain tokens for some use cases yeah it is it is problematic and but well I'll get to addressing those problems in a moment but for many use cases it's not at all


to use Bitcoin as B as a utility ledger often what you're not transmitting is large amounts of Bitcoin back and forth you're transmitting data and in fact the value carried in the transaction is the data itself not so not the amount of Bitcoin that you're transmitting so in those sorts of cases where you might only have a few satoshis attached to a transaction dust amounts then these fluctuations aren't aren't really going to matter longer-term now of course payment use cases and and anything whether we're the Satoshi value of the


transaction is significant of course it does matter but I think that this is simply going to be something that will settle over time as usage picks up it's the the usage and the velocity of money in any currency that dictates how volatile currencies tend to be the US dollar for example is pretty stable currency because of the sheer amount of trade that goes on in and every day Killians and trillions of dollars every day so and it's not so much even the dollar value that's moving it's just the amount that it's moving around and how


much people need to to have an acquire to use it for something so that's a longer-term problem but I'm confident that it will be solved and in the meantime there are many of other ways to use Bitcoin ESPE question are there any plans to remove the 25 transaction limit well it's not the 25 friends actually limit anymore it's the 50 transaction let me answer is yes of course there is this is probably the most asked question that I get the unfortunate part of the answer is it's a lot easier said than done there's layers and layers of


of legacy code that had been added by BTC developers over the last 10 years that we're slowly gun picking we're getting very close though by the end of the year I will get my my life and my job on it that we will have it fixed by the end of the year there's a good chance that we'll have that limit substantially increased within the next few couple of months is there a place where you can get information about bsv scripting how it works how to program it and capabilities I would say probably one of your best resources is forgive


the shameless plug the upcoming Def Con because there's at least two two presentations that are going to be specifically about Bitcoin script in different ways that you can make use of it now while there's a pause there was a comment earlier on somebody pointed out that I had a small little network on my wall I just thought I might show this because it's taken me almost a year to actually get funny in them I don't know if you can quite see see that there's a little bit of a hint as to what this actually is so this is actually an image


of the Bitcoin SB network seven days after the hash ball in November 2018 it's a limited edition because one of our senior architects who collected the data and built this diagram gave it to me and then I made him delete the file so that it would have some some rarity value going forward in the future can we get does limited transaction outputs reduced or eliminated Steve you certainly can and it's simply a question of when or if we are again actively working on this and by way of working on a feature that sort of goes hand in hand


in this which is enabling what I call consolidation transactions to be free that is where you have a large number of of inputs spending into a small number of outputs by doing that you're actually reducing the size of the UT Exocet which is a net benefit to miners so it makes sense to give them the option of that being able to be done for free and that opens up a world of different use cases very very micro payments you could offer a service that someone as a guess of value add to an existing transaction where someone just


adds even or once atashi output to you as a third party service provider and now that's not very useful on its own but if you sit there and collect them and ask them once you've got a thousand or whatever then now you just make one of these free consolidation transactions and put them together into a into a single amount that's actually useful again how to build simple web app on top of the blockchain three seconds how long is a piece of string a really good way to do this is to go join a hackathon or something like that there's a lot of


helpful people around that will help you one of the quickest onboarding libraries I suppose that I know of would be money button there's others that reducing other things but it's one that I know well so go take a look at their API and I know people have built an application in less than a day using that will there be systematic courses for beginners in the future let me address that one Bitcoin Association one of our key initiatives for this year and next year is really what you're seeing - a lot on developer education and training


initiatives so ladling Wilson is our technical program manager overseeing this the answer is use we will be launching later this year a variety of online training programs one in conjunction with the Technical University that we're partnering with and they're just put up by Bitcoin association with a goal of providing both basic Bitcoin training for developers and then moving to a more immediate and at the youth levels allowing developers to complete online uses through an online education curriculum take assessment tests and


eventually we want to a certification program to be able to survey developers at different levels of things upon the completion of our online education so look for more information about that later but I'll be coming and launching later this year Steve do you have any comments I think he means is that the maximum browser I think that's what that question means I have not actually had a chance to look at the maximum browser myself in depth and in detail but one thing that suppose that I will say about it is that it is at least


a year or two ahead of when I expected it to be not maximum specifically but a browser that was geared toward toward another Net Applications I thought this was going to be something that would take quite a long time for someone to build so the approach that the team has has taken I personally think is really impressive I I look forward to seeing how other people start integrating its and and making it part of the the daily Bitcoin kind of user experience yeah I encourage everyone to download the master six beta test it out check it out


play around with it I've started doing myself and a Jeff Kenya's team are definitely open to any feedback comments it's just a start and they're willing to take all kinds of suggestions for for that related to maximum Jeff and his team are also launching something called NB domain which is creating a new form of domain system for the watching like we have a you know internet URL the main system he's leading a initiative to create a new domain system for the watching world so I think that's really fascinating to watch as well Steve will


be a better alternative for all op return or it's the final solution will there be a better alternative certainly not the final solution there's there's plenty of other solutions out there right now one thing that I'm kind of hoping people will start to explore in the near future is embedding data in in spendable outputs for example some people are familiar with some basic scripting the typical paid a filmic key hash type of script all you need to do is put an opportunity end of that script and then you can put more data on the end of it


or before the script you can push data and then drop it again off the stack straight away is another way to embed data so that solves one problem that a lot of people I think have bitten there's been a lot of debate hot topic on Twitter lately what happens if minors don't keep all of that well as one solution is put it in a spendable output and they have have no option they'll probably charge you a higher fee for it that but it shows that there's many choices and many ways to do things in Bitcoin what I can say is up faults I've


returned point never go away it's possible now we're not going to be changing the protocol again so there's nothing to stop you from using it that way if that's how you want to what are your favorite BSB projects jan what a tough question Rhian it's um it's like asking someone a parent to choose among their children what are our favorites there are so many great ones out there so I I personally can't name what obviously I think things in each or Davis pilot project to use the blockchain for opioid pharmaceutical


prescription management and creating a bigger mission the global electronic health record so that consumers patients can be consumers of the health care data and monetize their own healthcare data I think that is fantastic because it demonstrates really the much bigger control and vision of what a global blockchain can be beyond just a payment system that's just one of my many many favorites and the other answer is anything Steve shadows does Steve you have any favorite you and I mentioned I have any favorites I mean there's a lot


that I actually think a really impressive eschatos is is one that that's really not my socks off so much so that inspired me to start my own my own weekend project doing something kind of similar bit ping formerly known as Optimus v not a fan of the new name that I understand that I was just asking for a trademark or on the track I think that's a really clever way to to make use of Bitcoin s being you know coder I mean I was on the judging panel for the two hackathons and those two one you want a couple of them


so so there's people who don't know what bit ping is it's a crowdsource and essentially network intelligence for monitoring website up and down time as well as other services on that use you know user mobile devices and devices around the world to provide that information we don't manage on the blockchain yeah do you plan to support hey ID parody if I recall rightly I think this is a an identity mechanism that was recently released and available it's meant to be sort of the payment mechanism agnostic it addresses BTC of


the dresses ACH transfers and a whole bunch of other things when I plan to support it well I don't have any business that the personally needs it but do I think that a standard that promotes interoperability between payment systems is a good idea to DSV to support yes yes I do interoperability will help people to onboard on to the ESB and if a bunch of user facing applications are implementing this standard that it makes it much easier for those applications to integrate with us be in the future so yeah that note I


take this moment to mention for our audience that one of the initiatives Bitcoin Association has launched and recently announced the initial committee members for it is a technical standards committee for Bitcoin SV we know that technology develops much more quickly and grows if there are interoperable standards so Steve is chairing the technical standards committee to evaluate just this exact kind of topic in many areas what standards can be recommended so that developers and businesses who are creating applications


the Bitcoin has to be world can create things that communicate interact and interoperate with each other we think that's really vital it's one of the things we're doing to lead the initialization of the coin where would be the best place that I could talk to others about up coming up with ideas for the hackathon Steve there's a lot of different forums where where our application developers hang out of course the hackathon itself has its own discord channels where you can you can probably reach out to other devs and I


think that the platform itself has facilities to help you with finding teams but outside of that there's there's a few telegram groups there's the Atlantis slack that's run by an Rider which is a common hangout for for developers I mean I don't have a huge amount of time to sort of hang around in all of these these various places so there may be it may well be others that I don't know about but here is a good place to start we'll go to any one of those and ask other people generally people are pretty friendly and willing


to only to help you people get on board Thomas asks do you always have to compare hash outputs to create a locking script based on a push from TX or is it possible to unlock without knowing in advance exactly what the output will look like I spotted this question and I'm still trying to work I mean I know that you're talking about off push TX and hashed outputs is a part of the seek hash algorithm so this is a very very technical question but I'm not quite sure what the specific use case is that you're what you're thinking of on push


TX's is a technique that's quite close to my heart because I've been forgive the pun that I've been not pushing it for the last few years and it took a while for someone to to grab onto it and actually try to implement it so I might take that question on notice so that I can actually give you a sense I answer rather than a been trying to guess what your what the question means and getting it wrong oh wow Henry what a question how long shatters until ESP transactions per second rivals that of MasterCard and Visa Steve give us a


definite time well I mean in terms of capacity we're pretty close the the long-term average number that has been cited for the whole lifetime in Bitcoin is 1700 transactions per second and we know that in in in short bursts of a few hours that the the SV network is already capable of handling that their peak capacity is quite a bit bigger but that's that's about 50,000 that's probably going to take a leap beyond the Bitcoin SV note software and into tera note their Bitcoin is we may may may be able to achieve that sort of unsure but


I'm personally working on tera known proof of prototyping myself it's one of the few projects that that I dust off the old old keyboard and and get in and code myself but I generally don't have a lot of time for coding because I'm too busy organizing things and then chained that we're making really good progress with that and I'm looking forward to doing some demonstrations of it as soon as as soon as I can I'm gonna get myself into trouble if I name any kind of a date because also get held to it but I would like to be demonstrating it before


before the end of this year and for audience members who don't know what tera node is it is an enterprise class version of the Bitcoin SV node software that is designed to support as the name suggests terabyte size blocks you know your megabytes plus for massive massive scale Steve and team leading at first initially to reconstruct the Bitcoin node software from the ground up using a microservices architectural approach to create far more efficiencies well look for more information about that coming in the near future


when will the courses for bitcoin engineer start I don't have an exact date and the but I know we're hoping to launch our partnership with a tech University for a massive online open course sometime in the fall of this year we're on October hoping and then our Bitcoin association for more online education curriculum we're hoping to get some of that play and beer do you have a timetable for change in a DAA the difficulty adjustment algorithm Tim Donovan gosh all these probe questions Steve what do you have to say about that I I get asked


this one a lot and honestly scratched my head sometimes wondering why people are so interested in it because it doesn't really impact the for the day that they user experience all that much the one thing that is notable about Bitcoin SB is it actually really doesn't matter if we go for an hour or even two hours without a block because when one eventually gets found everything just gets cleared out in one one hit so but the answer to that question is it's it's dependent on transaction volume because the olds 2016 blaack difficulty


adjustment algorithm creates a vulnerability for a lo hash rate chain which we call chain death attack whereby someone comes in with large amounts of hash rate from somewhere else pushes the difficulty way way way up and then goes away and if you're in a situation where it takes 24 hours to find a block well that two-week period is actually measured in blocks so it becomes 2016 times 24 hours and that's not an ideal situation to be in but when you've got large amounts of transaction volume coming in and fee revenue it changes


that dynamic completely so we've been doing some studies internally on what different levels could create what sorts of scenarios in terms of if someone tried to pull off that sort of attack just to determine where the where the kind of safe level is and I've got some answers on that I'm there are security concerns which is why I'm not just bloating everything out but I know about right now and I think carefully about about how to approach this from a public discussion point of view because it doesn't in public


discussion but I think their short answer is it's definitely not going to be this year my guess would be it would be probably some time probably not before middle of next year and maybe you know towards the end of year but as soon as we actually have enough data to be able to say yeah it's the it's the right time to do it or at least plan it and start setting a date then then we're talking about it publicly and getting as much public feedback as as possible we are like coming to the end of this time boxed the answer a last question or one


that question then everything which comes after that is something I will forward to you and see that we get answers published so everybody can see that so on the last question is what do you see as the next steps required for the wider use of micro payments hmm steam you want to tackle that sure so a lot of the building blocks are either coming her either in place or there they're just sort of coming into place and a lot of this comes down to that animation that I showed you near the beginning of my presentation which


governs the flow of a payment interaction between between two parties so there's multiple parts of that there's how do I find the person to connect to them directly which female is one of the potential will be at one of the solutions to that there's how do I get the transaction directly to the miner promptly and find out that it's definitely being accepted the merchant API is a component to that the floral of that even happens though there's the the negotiation between the the merchants are selling and the customer


and that's part of it 270 so all of these components are coming together and of course they need to be implemented not just by miners or any particular service but all of the bollocks as well so they can operate happily together so completing the work on all of those steps I think basically defined what that pathway is how long have the tape and I'm not sure because it requires work to be done by a bunch of people that can't me who I don't I can't compel them but there seems to be a pretty strong appetite amongst many of the


wallet applications to get on board with this and a lot of works already been done so I'm pretty happy with burgers that's the thing technical behind-the-scenes answer I think from a practical industry and because it's super effective the answer really is developers like all of you on this one program who are listening designing creating conceiving great applications has drive people to want to have some functionality that uses micropayment something like coda or developers can make money you're an API marketplace so


it's the ingenuity and the creativity of developer creating really powerful applications have real utility things people want to use what do they even know it runs on Bitcoin or not that leads to real usage so we encourage people to just get building that's what we really believe in in the Bitcoin ESP world building a blockchain and the digital currency with real values we build complete useful applications that will make people want to use them and that will drive micro payments and Deitrick cool so thank you Jimmy thank


good evening everybody my name is rose I'm with the Academy of Science st. Louis and we are one of the sponsors of tonight's talk along with the st. Louis Zoo and we're very pleased to be partnering with the zoo to bring you tonight science seminar before we get started this evening I'd like to tell you a little bit about the Academy of Science and who we are we're an independent science organization we're supported entirely through community contributions and we've been around for a very long time since 1856 it's our

Reversing Time, Photoacoustics and Other Optical Breakthroughs in Biomedical Imaging


mission to promote the public understanding of science and inspire the next generation and at venues throughout the region we do that by connecting science in the community through free and our very low-cost public talks so in seminars and workshops and trips and tours that celebrate science at venues throughout the metropolitan st. Louis region and surrounding counties these trips tours and talks feature scientists and engineering professionals of both national and international renown in addition to advancing the public


understanding of science excuse me as I had said it's our mission as well to inspire the next generation we do that through a number of free and low-cost opportunities that are expressly for teams such as their teen science cafes teen cafes Youth Leadership Council and Junior Academy of Science the Junior Academy is a pre-professional stem membership organization for students in grades 6 through 12 that offers hands-on opportunities in science engineering and medicine teens can attend unique behind-the-scenes explorations of


leading engineering technology and science labs of our region you can access University Libraries participate in field opportunities in challenging and engaging science competitions for a full range of academic levels and Junior Academy members make real-world connections meeting top stem professionals so if you know a student or students or you are a student in grades 6 through 12 with a love for science memberships in the Junior Academy make great holiday gifts you can find more information on the Academy and


all of our community wide events by visiting our website at academy of science stl dot org you may also visit us on Facebook or Twitter or before you leave tonight pick up some of the literature that is on the table just outside the auditorium I do want to mention a couple upcoming academy events you might have an interest in attending on Tuesday evening December 9 at the Missouri History Museum retired University of missouri-columbia associate professor of fisheries and wildlife sciences and the Nature Conservancy's Great Rivers


partnership science advisor dr. David gala talks about an ecological history of the Missouri River and 21st century challenges in the Big Muddy this event is free and open to the public you do not need to register to attend and then on January 28th on the Washington University Medical School campus and as part of our teen science cafe series radiology and biomedical engineering professor dr. Susan Lackey talks about nanotechnology in the science of the small teen science cafes are open to all students in grades 6 through 12 they are


interactive they are free and there is food but you do need to register to attend and you can do so by logging onto our website again at academy of science stl org you can find even more science opportunities talk some tours on our web site or listed on the event fliers and Academy literature that is available for you to take with you before you leave this evening if you'd like to receive a notification of upcoming academy public lectures and events there are some enews sign-up sheets that will make their way


around the audience if you are a student and you need to verify your attendance at tonight's talk there will be some verification cards that are available following tonight's QA also out at the table outside the auditorium please turn off cell phone rings or any other electronic devices that might make noise during the program with all that said I'd like to introduce this evening speaker dr. Lee Hong Wong dr. Wong earned his BS and MS and optics from Zhang universities of Science and Technology in Wuhan China and his PhD in


electrical engineering from Rice University he is a fellow of the Academy of Science State Lewis and a recipient of the Academy's 2014 James bees outstanding st. Louis scientist award recognized for his seminal work in photoacoustic tomography and bio photonics he is currently the gene K berry distinct professor of biomedical engineering at Washington University in st. Louis and his book biomechanical optics principles and imaging was one of the first text books in the field garnering the 2010 Joseph W Goodman book writing award dr.


Wagner is also the co-author of a book on polarization and editor of the first book on photoacoustic tomography his laboratory invented or discovered get ready functional photoacoustic tomography 3d photo acoustic microscopy the photo acoustic Doppler effect photoacoustic reporter gene imaging focused scanning microwave induced thermoacoustic tomography universal photoacoustic reconstruction algorithm frequency swept ultrasound modulated optical tomography time reversed ultrasonic Lian decoded optical focusing


sonoluminescence tomography Miller matrix Oct article coherence computed tomography and oblique incidence reflectometry his magic Harlow model of photon transport and scattering media is used worldwide he has published over 380 peer-reviewed articles and delivered 382 keynote plenary are invited talks he is prolific and well-known across the globe and we are very pleased to have him here with us tonight he's here with us to talk about photo acoustics and other optical engineering breakthroughs in biomedical engineering on behalf of the


academy of science news in the st. Louis Zoo won't you please join me in welcoming dr. Lee hongwol well thank you rose for the very kind introduction thank you all for coming here tonight I'll be talking about several technologies we've been working on in our lab our goal is to image biological tissue using optical contrast starting from the motivations and challenges in our field in general I'll be talking about two major incarnations of photoacoustic tomography namely photoacoustic computed tomography and photo acoustic microscopy then I'll talk


about some some of the newer technologies we've been working on time reversal and compressed ultra-fast photography the very first question is why do we bother with light for imaging purposes you know when you walk to a hospital you go to your video department you'll see a lot of imaging modalities already MRI ultrasound and x-ray what not now first of all it's very safe to use light because we're receiving light or optical photons all the time every day so we're dealing with what's called now ionizing radiation the radiation


involves photons of very tiny energy you're talking about electron volts as a unit for photon energy so when you're talking about a cup of v's then the photons are not energetic enough to ionize molecules very safe but we use x-ray photons that are so energetic thousands of v's they'll knock off electrons out of molecules do eyeliners tissue and cause problems such as DNA DNA damage and so the ionizing radiation parted of the EMR electromagnetic spectrum causes the problems right so we're working this region which is very safe more


importantly from a very fundamental perspective which is the physics that tells us light occupies a very special region of the EM spectrum this is the only part of the EM spectrum that allows us to probe molecules directly so we have access to the molecular information we know the importance of molecules in biomedicine right so we have to use a light and because light can probe molecules we can apply this to biomolecules all the biomolecules you can think of right you can read the four major classes of biomolecules some other endogenous or


intrinsic biomolecules or even exotic molecules you know later on I'm gonna make a point that in fact by using photoacoustic tomography week we can potentially image any molecules right so this can be extremely powerful by using by imaging biomolecules we can provide all sorts of imaging functionalities for example in vivo functional imaging very much like functional MRI you might have heard of so x-ray will image structure very well but x-ray may not be able to tell if a piss piece of tissue is alive or dead right so we want to image not


just the structure of the tissue but also the physiological function and photo acoustics or optical imaging in general can provide that type of information in vivo metabolic imaging so this is someone like PET imaging positron emission tomography you know we're looking at metabolic parameters right so I enumerated a couple of examples such as the metabolic rate of oxygen glucose consumption rate we all know that these are the two major mechanisms of metabolism your body right in vivo molecular imaging so we're able


to image all sorts of biomarkers which can potentially be hallmarks of cancer for example and we can image reporter genes that allows us to track gene expressions we can even provide label-free in vivo histological imaging as we know standard histology is invasive you know when you go to the hospital if physicians who we need to do a histology on you that means they have to exercise tissue out of you all right so that's invasive then they'll go through a series of procedures and prepared a tissue before they can examine the


tissue slices under microscope so the whole procedure is ex-vivo invasive and takes time can we move this technology and transform this to an in vivo situation where we can look at a tumor margin right as we know that a lot of cancer patients die because the cancer cannot be removed 100% so there's small residual of cancer cells and that are left around right so then the cancer will grow back can we use our technology to demarcate and basically find the boundaries of the tumor and remove the cancer 100% so that's going to save lives there are


many many reasons why optics is so powerful but we face challenges one of the challenges is called diffraction right in high school or middle school we were taught that you can focus a light beam through a lens to a geometric point all right if you say that in a high school you get a full mark right but if you say that in college the professor may tell you you're wrong right so because light is a wave anyways cannot be focused to a point a geometric point right the ultimate size of the focal point depends on the


wavelength right in this graph if you do your best try to focus as sharply as possible make this angle alpha 90 degrees your focus eyes will become wavelengths over - right that's how small you can focus this is called the diffraction limit so waves water fracked this year three of our colleagues working in our field were awarded the Nobel Prize in Chemistry actually for breaking through this limit so this limit has been come they can generate resolution smaller than the wavelength which is amazing achievement now we face even


more challenges in penetration right our intuition tells us light will not penetrate through tissue because we can't even see through our own palm right so when we close our eyes our eyelids is going to block all the light we can't even see the outside but you will actually see light right this is why some people when they sleep they have to wear blindfolds you have to wear blindfolds our eyelids are not dark enough they're not blocking enough light right so photons you know basically it's a quantum term for light photons will


actually go through the eyelids and reach the retina and this is why even when you close your eyes you will see some light where's the challenge if we want to penetrate penetrate tissue and get images 350 years ago microscopy was invented right that really revolutionized medicine or any previous before that point there was no technology that allows us to see cells with the Y field optical microscopy we can see cells now we're at micron resolution however you have to cut the tissue into very thin slices like ten


microns in thickness and this is still the standard technique for histology or standard pathology analysis so what I call the penetration limit in this case is the operation right so the way from distortion in order to form a very good image you have to have a very regular wavefront you have you have a controlled wavefront so in tissue because of the distribution of the refractive index in other words the speed of light will travel this light will travel at different speeds of light depending on which part of the


tissue lion is traveling through and that gives you a problem that's gonna cause distortion and preventing us from forming a good image right so that problem was overcome about maybe 20 years ago using modern optical microscopy you might have heard of a confocal microscopy two-photon microscopy or even optical coherence tomography these are really modern wonders of optical imaging technologies those technologies will reject multiple scattered photons they'll retain the on scattered or singly back scattered photons for imaging and there was


sharpen up the images they overcome this operation limit in penetrate from the original limit of say a hundred microns to about a millimeter by the way 100 microns is roughly the diameter of our hair that's how small it is a millimeter you can picture if you have a little ruler you can picture a millimeter right so a millimeter doesn't sound very big but it's a huge advancement from 0.1 millimeters so 100 microns is 1/10 of a millimeter so that's a factor of 10 enhancement in terms of penetration right though those technologies have


impacted biomedicine enormously right not just for biology but they've also been used in medicine if you go to your ophthalmologist one day they may actually use Oct article coners tomography to examine the retina for you right because without Oct you can only see the surface of the retina you can't go beyond the retina there might be something going wrong sometimes it's behind the surface of the retina OCT is able to see through the entire resume layer very very powerful technique however this set of modern optical


microscopy techniques face the next challenge something I call diffusion limit right so they cannot go beyond one millimeter in depth in valid or tissue how do we overcome that problem so we use photo equipment rasca viewer in general photoacoustic tomography to overcome this problem where we actually use multiple scatter photons so I have a little cartoon here conventional microscopy use straight propagating photons the modern optical microscopy will tolerate a little bit of a scattering because they can be checked


multiple scattered light but to go deeper we have only multiple to scatter light left so you cannot afford to reject multiple to scatter light otherwise you will get no signal so we have to use those tortuous paths for our light propagation and somehow we have to get spatial information right so that's the huge challenge because oftentimes when photons wander around through this tortuous path you'll lose spatial information so that means you're not gonna get a sharper image we somehow have to form a sharp image our solution


is to use photo acoustics and as a result we advanced the penetration not just by one order magnitude by more than one order magnitude more than almost two orders of magnitude now we're able to penetrate multiple millimeters even multiple centimeters so you're talking about not only skin level penetration but also organ level penetration I'll show you some more examples later like anything else we face the next challenge right we cannot penetrate beyond right now seven centimeters how do we target the next challenge this this limit is


called the dissipation limit because beyond this steps even the multiple scatter photons are spread around so they're not very intense even though you have a lot of photons at that kind of depth so the next natural question is can we gather those photons they make them intense okay so there's upcoming technique called the wave from engineering with the internal guy stars there's hope there there's hope that we can potentially break through this dissipation limit and reach the next level this could be extremely exciting


if we reach there because now we're talking about tens of centimeters of penetration by using safe light now we're talking about potentially whole body human imaging using known as a radiation with rich contrast information so very very exciting I'll touch upon this topic later on and this is ability to time reversal now of course the ultimate limit is the absorption limit if you take all the scattering centers away out of the body you all you have left is absorption right so that's gonna limit your light penetration likely if


you use the right light wavelength the right light color that penetration is extremely long it's like a meter or so right all right so let's take a step back and ask yourself the question what does it take to get a good image if you we all know how x-ray chest x-ray works right chest x-ray works so well because x-ray does not scatter so much in tissue you get what's called ballistic light ballistic photons in x-ray regime so that's gonna cast a shadow directly for you and you can see that the bones and certain structures if you mimic x-ray


projection by using light when you have certain tissue thickness you're not gonna see see a shadow at all right because light will follow a highly tortuous photon path before reaching your observer right so on this side you won't see a shadow if we surgically cut open a tissue right that's invasive of course now the right hand side is well very well defined because this is all exposed to your error in the photon path will be well-defined allowing us for two form a very good image despite the torch was fallen paths on the left side so the


point I want to make is you only need one sided clarity you don't need both illumination clarity and detaching clarity well this is so invasive it's not very useful right a better idea is called optical clearing so we can introduce certain chemicals into the tissue that's going to turn a tissue transparent right so that's going to achieve the equivalent to case P giving us a very sharp image unfortunately this process is toxic so you may have turned a tissue transparent but this is gonna kill the tissue so it's not very useful


for you vivo imaging what we are doing is to convert light or photons into ultrasound signals so we're talking about acoustic signals here through the photo acoustic effect acoustic scattering is orders of magnitude like a thousand times weaker than optical scattering equivalently on the detection side we've reached case P or KC without invasiveness or toxicity so on the detection site now we're dealing with transparency that allows us to form a sharper image so that's the basic idea behind this technology right let's see


I'll give you more demonstrations later on to make sure we understand the concept photoacoustic very much like x-ray CT there's also photoacoustic CT we have different geometries I'm going to talk about circular geometry first photo acoustics as a physical phenomenon has been around for over 100 years in fact Alexander Graham Bell first reported photo acoustics he actually invented the concept of photo phone right very interestingly this paper was published only a few years after the first telephone was built he had a site


you're building a photo phone using light to communicate so his idea was to encode the voice or music into a lie beam then propagate a lie beam in space convert light back into sound again you cannot you hear that so he had no access to laser at a time that he was way be the head of the time you know because laser was invented in the 50s right so he had to use sunlight to demonstrate this principle now this idea never quite took off right for reasons you can imagine because together to work you have to have a line of sight


communication right but nowadays we have laser this idea may actually take off again with someone you actually revive this idea later for secure communication we have the opposite problem 100 years ago right so telephone allows you to talk between neighborhoods you know without worrying about line-of-sight transmission but now we're worrying about security so between towers for example you know you have directed communication you don't have to you don't have to worry about you know losing your message right for security


purposes so of course in those days there was no concept of tomography right that was not you mean in the lexicon it's a totally new modern concept we're using this very old physics with a very new modern imaging concept to form a new imaging modality a very simple analogy I can think of for photoacoustic CT is how can we pinpoint a single sound source single point sound source like a thunderbolt so when we see the lining we can reset our stopwatch that would be our time zero when we hear the sounder we can record a time delay t1 multiply


the time delay by the speed of sound we will define radius first ergo shell on which lining took place if we have three such measurements Center at different locations we will have three spherical shells the intersection of the three shells will pinpoint the thunderbolt right so photoacoustic CT in essence is a straightforward as this its triangulation right something we learned in middle school or high school right you can triangulate geometrically you can figure out the source right except in a real situation we don't have a


point source we're gonna use light to generate a volumetric 3d complex source we don't know the exact source distribution because the source distribution is the image we're after so we have to use more than three detectors but this gives you the basic concept at the simplest level so for photoacoustic CT the first thing we do is to expand the laser beam very different from a common use of laser where you want to use a very high intensity to drill a piece of metal for example so when we talk about laser you say well that would


be dangerous you know this is a laser beam here I want to have high collimation this is not very high power so the first thing we have to guarantee is safety what we do is to broaden the laser beam make sure the light intensity is within the safety limit so there's this institute called ANSI that regulates the safety of laser use if you stay within the safely safety element you're very very safe light will be scattered around so if you want to image deep you have to tolerate light scattering we actually allow photons to


scatter so you can penetrate multiple millimeters even multiple centimeters in biological tissue when light is absorbed it generates some heating we use very short laser pulses nanosecond right one nanosecond is a 1 1 billionth of a second right very very short laser pulses so this heating is very very rapid and we don't need a lot of heating milli degrees right so one one thousandth of a degree would be adequate that will give you a detectable signal already so if you generate hundred hundreds of milli henries of million agrees then you have


a very good signal to work with that allows you to form a bright image so this transiting allows us to generate ultrasonic emission is going to generate Christic wave through the photo acoustic effect okay so this is the bells effect and because of the acoustic transparency we can detect all the acoustic signals and form a very sharp image outside however the contrast comes from optical absorption so we're combining optical contrast without drisana krez Ellucian these one common question is why don't we use ultrasound tomography why do you


have to use photo acoustics so you notice on tomography as you know you actually fire ultrasound pulse into tissue then listen to the echoes right so medical ultrasound imaging originated from sauna of sonar right so after the Second World War scientists and physicians started to borrow that technique in a pointer for a human imaging so what ultrasound imaging does not provide is the optical contrast we want to have the optical mechanism as the contrast so we have access to molecular level information for example


using light later I'm going to show you we can see the color differences of the two forms of blood oxygenated blood and deoxygenated blood red versus blue our veins you know look blue right the arteries will look red so ultrasound will not be able to tell the difference that's just one example this is the first set of functional photoacoustic images it's also the first set of in vivo images acquired using photo acoustic CT this was reported in 2003 by our lab and we can see actually brain activation if he we go one side of the whiskers of


assam animal and the contralateral side of the brain would be hemodynamically activated so the blood flow will change and we can detect that change to show the brain activation on one side and those images were acquired now evasively so this work really started the growth of our field you know if you look at after 2003 our field really doubled roughly every three years in size after 2010 the conference on this topic became the largest in photonics West which is a twenty thousand attendee gathering right so this has surpassed a lot of the


competing technologies or you know peer technologies a natural question is why is this technology so exciting well this is probably the only technology that allows us to image from organelles all the way to organs in vivo and we use the same contrast right so we use the optic absorption as the contrast mechanism so I'm plotting different implementations of this technology right we actually have far more than that can pot here but this says this is a highly scalable technology we can image at very much microscopic level but we can also scale


to the macroscopic level this type of multi scale imaging can be very very important because in current medical practice or biomedical practice for cells and below we use optical microscopy so we're acquiring optical contrast but for tissues and above we switched to now optics we're gonna use MRI ultrasound x-ray CT what have you so we're talking about two different contrast mechanisms mechanisms preventing us from correlating images across all the lens skills as we know to understand about the problem we have to have a multiscale


understanding you have to correlate information across the learn skills so photo tomography can potentially allows us to do so by enabling multi scale biological research and enabling translation of microscopic discovery to macroscopic clinical practice at least accelerate the pace of such translation so for the 2003 work we actually use a single element transducer that took like 20 minutes to get a 2d image now we have ultrasone arrays with 512 elements within 2 seconds so we can get a 2d image in fact now in our lab we're


building a system that allows us to get an image within one millisecond so the technology is really getting faster and faster in terms of data acquisition so we can image the whole body of its Manimal right without without injecting any contrast agents we can see the internal organs we've got 10 defined boundaries detect tumors detect functions the farmers are very interested in in this type of technology because what is the alternative to see this type of contrast they have to use x-ray CT the radiation dose is a big problem to monitor the


same animal for development of a new drug you have to monitor the animal multiple time points over a time course of a couple months at least so the radiation dose can kill the animal and it doesn't give you enough information as well because x-rays sometimes does not provide enough information right you have to have the functional information to make your to test the efficacy of the drug further acoustic tomography is simultaneously analogous to MRI in pet so this is one example on this site we can see the hemodynamic contrast


right so this is the concentration of hemoglobin we detect the brain again in response to electric stimulation of the pause of the animal on one side you can see the counter lateral side of the brain activate so on this side we're showing why this is analogous to PET imaging so we're using a glucose analog that mimics glucose so when there's glucose uptake you can see stronger signals right this is very much like PET imaging so this can be potentially very powerful in the future as well because photo acoustics can serve as a backbone to


connect with other standard modalities like MRI and PET we're trying to push bring image into the ultimate level human brain imaging this is extremely challenging problem because human skull is a lot thicker than animal skull so that causes problems because the skull has a different speed of sound and soft tissue so this is like a photograph of the x-ray CT image X X we go a tall skull and this is a photograph and we put this k9 brain inside this skull which are the image using photo acoustic tomography actually some of the


colleagues predicted this will not be possible because the skull is so thick we got very very encouraging data so we got a image that shows certain structures which match the structures in the photograph very well the next big step is to push this to in vivo imaging of human brain unlike x-ray CT which always works in transmission mode because x-ray doesn't scatter much further acoustic waves propagate essentially in all directions so that means we're very flexible in terms of actually implementation I just talked about the circular geometry for


detection but we can also do it using a linear geometry so this is a hand hold ultrasound probe that you might have seen the hospital we have like hundreds of ultrasound detectors along this probe we use optical fibers optical fiber bundles to deliver light with a single laser shot we can illuminate a volume below this linear probe it allows us to form a two-dimensional image so all the data will be acquired within say 100 microseconds so your boy motion artifacts when you acquire this type of images and you can


see this is actually a standard ultrasound machine we worked in cooperation with Philips to modify this clinic ultrasound system for concurrent photoacoustic imaging yogic dual contrasts for the acoustic contrast in ultrasonic contrast so this system works around this point allows you to penetrate multiple centimeters and get hundreds of microns resolution this is a one example where we can see a tiny absorber buried at a depth of five centimeters right this was not possible using standard optical imaging right at


this type of resolution in fact this is a form of reporter gene imaging or a form of molecular imaging again three colleagues receive the Nobel Prize in 2008 for their discovery of force and proteins you might have heard of you know this is a huge discovery that allows us to follow gene expressions but it's all fluorescence based by using standard optical imaging you cannot penetrate these so all of the applications are limited to cells or animals at a very shallow depth now we're talking about multiple centimeters


of penetration for this type of imaging so this is going to extend the capability of fluorescent proteins and some of the derivatives this technology is being tested at Washington University for a human studies for human applications and this is one example where a breast tumor was imaged using standard ultrasound imaging and photoacoustic imaging we can see the CM tumor using a very safe light dose the laser intensity is one-half of the safety limit and a safety light safety limit is less than one-tenth of the dams threshold so this is


extremely safe level light those we're also targeting something that might have a more immediate application which is breast cancer staging you might have heard that the standard breast cancer staging is invasive you have to surgically remove the first draining node or the central nerve node what we want to do is to inject organic dye near the tumor it's gonna flow toward a central enough node then we use the photo acoustics to detect us in the lymph node and use a needle which is guided by the photo acoustic technology


to take cells out of the simple nerves node do you test if there's any presence of cancer cells so once this is a proven we can convert the surgical surgical procedure into a needle biopsy procedure this is some of the initial test results in humans you can see the central nodes note we can see the needle here at as well in there another clinical problem is to monitor the brain oxygen consumption in the surgery you want to do it in the war but there's no non-invasive technique allows us to do that well so the current technique is


invasive you have to insert into the carotid artery and jugular vein some sensors to detect the oxygen content so can we do this now you massively we can use photo cosec tomography to quantify the oxygen saturation we use so2 to represent the oxygen saturation level at both the caudate artery in the jugular vein and you'll see that they have different values the difference in so2 tells you how much oxygen has been extracted by the brain so this is an indicator that tells you how well our brain is consuming the oxygen if this


difference is too small that means the patient is not consuming enough oxygen are you going to do something about it otherwise the patient might wake up from the surgery bring that so we've tested seven healthy volunteers that reach so2 is very similar to the expected range so this is very good news for us as a initial test the next natural step is to move this into the war to work on real patients let me move on to the microscopy domain unlike the photoacoustic CT you will have to use math to form an image you know you have


hundreds of sensors that Christic sensors you get all the signals then you send the data to a computer use your algorithm to form a image someone like x-ray CT image reconstruction but it's actually more sophisticated because it deals with extra dimension so here we're gonna use acoustical lens very much too like lenses like I'm wearing a pair of lenses and everybody has a pair of lenses Eve even if you don't wear glasses right our eyeballs actually have lenses inside as well these are biologically made so here


we're gonna use the acoustic version of lenses to firmly image it directly let's just assume there's a target you know a piece of tissue we want an image we fire a light pulse to illuminate the tissue to generate photo acoustic waves and then we use this focused ultrasound transducer to receive the signals and you're gonna get a time trace like this so this is your time axis you get a voltage like this you'll see a spike corresponding to where the target is so if this guide is deeper then this spike is gonna appear later if you have


multiple absorbers or targets you'll see multiple spikes because we know the speed of sound in tissue we can convert this time of arrival into depth so this time trace is essentially a one dimensional image we call that a scan right or 1d image if we scan the system across the Tish we got a 2d image you would call that be Skinner right now if you're Astros game on a tissue surface you got a 3d image so that's the basic concept and this is the detail now maybe I should skip this is this photograph shows the first 3d


photo microscope which we published in 2005 so this is used to implement the idea I just described right so we focus light into tissue right to penetrate deep beyond like a millimeter which is the limit how far how well we can focus right beyond a millimeter you can't really focus so well and so we use this what's called a dark field we use a done' beam on a surface to minimize the surface interference and then the ultrasound transducer is comfo wholly located you just want to maximize your signal strength with a single laser shot you


get a 1d image in the depths duration so this head is raster scan XY scan in its water tray to get a 3d image so this is the map rates around this point it penetrates three millimeters we can scale to a few more millimeters if we won't add expensive resolution everybody you can get tens of microns resolution so the resolution is getting better this is an image of our own skin in this area of the palm there you can see blood vessels without injecting any contrast agents if you want to get the same type of images use x-ray you have to inject


iodine base contrast or some other heavy metal phase contrast even then you'll miss some of the smaller vessels because x-ray does not give you enough contrast for vessel imaging so we all know the importance of blood vessels this is a depth result or be scanned image showing you some of the standard skin structures now we're working with our dermatology department you apply this technology for melanoma imaging we've also miniaturized the probe so we can use this technology in the GI tract all right so you have to make the device


tiny in order to be inserted into the standard endoscope so unlike standard endoscopy like colonoscopy for example which only detects the surface of the lumen or the colon right so here we want to image beyond the surface these standard colonoscopy or upper GI endoscopy will miss anything beyond the surface we want to see deeper right seven millimeters is sufficiently deep in terms of the GI wall right so that allows us to see the deeper structures by providing both photo acoustic and ultrasonic contrast mechanisms so this


technology has been licensed to a large company for human translational commercialization I'll skip some of the details on the engineering side and this is by the way this is the first photo Costa endoscope we can also implement a photo acoustic microscopy at even finer resolution so if we sacrifice the penetration now we're back within one millimeter penetration these we do want to cover the very top layer of the of the thickness so you can focus light more tightly that allows you to get finer resolution and you do have to


somehow collect the ultrasound wave so we have to engineer this transducer or beam combine or what we call light some combiner that allows us to combine the light optical axis and acoustic axis make them coaxial right so with a single laser shot you get an image 1d image and then you can raster scan to get a 3d image so this technology works around this point right so your penetration is about one point two millimeters but you're getting a single-digit micron resolution so this is one example where you can monitor the same animal over time so


this is angiogenesis meaning new growth of blood vessels right so we can monitor this process because angiogenesis is a hallmark of cancer cancer cannot grow without growing more blood vessels so it's a very important process of cancer growth and of course this is just the one side of the story the flip side of the story is we can potentially we're actually doing that we're using the same technology to monitor drug the targets angiogenesis so we can use this as a therapeutic technology now therapeutic you use the anti-angiogenic drug to


treat into genesis and we can monitor the efficacy of the drug this is another example we can see essentially every single blood vessel in the skin including the smallest capillaries you can see here these are capillary pads you know the lines are single capillaries that are actually single of ourselves so we're looking at single cell lab already using this technology without injecting any contrast agents this is all what we coin dodged in this contrast we can also detect the color you know because our C and D arcy


hemoglobin molecules have different colors right so we can quantify the concentrations of both forms from which we can compute their oxygen saturation of hemoglobin right this is a very important parameter and we can detect arteries and veins by looking at the colors and this is actually coming out of our finger cuticle so we can image a human capillary loops and watch the color of the blood vessels and that tells you where oxygen is released the most it turned out at the tip of the capillary loop seems to release most of


the oxygen right so this is very interesting physiology in one day we can potentially use this to monitor some of the diseases involved in in human capillary level even some of the diabetic applications we're trying to push this photoacoustic oximetry to the ultimate level right this is the device working at 1 Hertz just for demonstration purposes this is 20 Hertz and we actually work at 200 Hertz at this rate we can see single red blood cells traveling right so you can resolve single red blood cells in real time in


vivo and watch how red blood cells bifurcate at this Junction we can also look at the color of each red blood cell and look at how oxygen is released from red blood cells as we know red blood cells are oxygen carriers so this is the ultimate level oximetry it allows us to study some of the fundamental biology related to oxygen delivery and of course this is very much relevant to to cancer metabolism now this is very recent the data is unpublished as we know cancer primary tumor will not normally kill patients is the metastasis that kills


the patients so when the primary tumor somehow transported to a distant site that grows a new tumor and a grow to grow everywhere that kills the patient so CTC or circulating tumor cells are very important because this is one mechanism where cancer cells spread now we're able to monitor you'll see these flashes of white ash these are circulating tumor cells if we can man identify them in the bloodstream right you can do multiple things to stop the metastasis right you could well you can imagine that potentially you can


simply zap there's circulating tumor cells using a higher energy laser pulse that would be a Wang approach there are certain other pharmaceutical approaches you can think of I talked about histology right so how can we make standard histology now invasive in vivo and we can actually detect the cell nuclei directly by using photo cosa microscopy we get an image that looks almost like standard HD staining histology so this is the standard histology this is the same piece of tissue that we acquired using our native


contrast we use the optical contrast so we can potentially move this into the o.r and find out brain tumor margin for example right so that can potentially improve patient survival we also try to beat that wavelength limit for resolution so you can see here this is the stander microscopy at a very fine resolution already but we improve that further to a resolution of 19 an au meters so this is sometimes called super resolution imaging we break through this wave lens however to limit for resolution now we're detecting mitochondrion we can


see some of the internal structures of a single metal counterion so now we're talking about this regime of resolution so so far I've demonstrated the scalability of photoacoustic tomography has applications in animals cells all the way to humans but we're also working on time reversal because eventually wanna beat the penetration limit the photo acoustic tomography go even beyond what's available right now so time reversal is possibly one solution this is a very very interesting concept you know the we are actually


inspired by astronomy the astronomers started something very similar because they want to observe the stars clearly but our atmosphere is going to distort the wave coming onto the earth so that allows actually pours the images what they do is the fire a laser beam to generate some sparks the sparks in the sky will serve as a guide star there is its artificial Chi star it allows us to correct the wavefront distortion as a result you can form a sharp image like this so it's very striking difference all right can we do the same thing in


biological tissue right so we don't have first of all we don't have a guys there how do we solve that problem in biological tissue well let me illustrate the time reversal concept using this cartoon let's say we have a tiger this there's a bottle of liquid right that's gonna cause way front distortion so if you have plane wave way from very nice way from on this side as a propagates through this bottle it becomes this wavy way from right this wave wave wave away from if it's reflected by this standard mirror like the mirror you use every


morning it's gonna cause basically return its way from it'll stay wavy and when you go through this bottle again it'll become even more wavy alright so the conventional mirror is not gonna give you anything that's reasonable it's not gonna give you a sharp image in fact you know by going through the bottle twice you get twice distorted you get an image that looks like a distorted tiger but if you use this special mirror something called the face conjugating mirror that's going to return the way frown in assert in the same direction


right so you notice here this way from curvatures are complementary to the from here right but this phase conjugate mirror is gonna return away from a in the same direction this is almost like a time reversal right the concept is like a time reversal you record some scene right if the person walks forward you play it backward the person is gonna walk backward so we want a wave we want an optical waves to walk backwards right so that's why the phase can't you mirror does right when you go through the bottle the wavefront distortion is gonna


be canceled through this bottle you get a very nice way from now you can see a very sharp image so that's the power of time reversal how do we implement the same concept in biological tissue we knew the guy star first of all to begin with which is really hard to do in tissue in the early days our field actually embedded some molecules into tissue that provides it guys that are the trouble is that's invasive you have to poke the tissue to you eject some dye or floor force and it's also not very flexible because once you have that


molecule in the location that's fixed you can only focus light to that position so what we do here is to focus ultrasound to a given point and that ultrasound is going to attack light passing through the outside of tissue we detect attacked photons and time reverse the tagged photons back and it will come back to the outer assumed focal point so this technology is called time reversed ultrasound coded or true optical focusing in other technologies to use photo quistis as a guy star right so this this is called optical speckle


right if you have a camera embedded in a piece of tissue this is what you would see in general yeah you got bright spots everywhere there there are actually a lot of photons down there even when it's deep but they're all spread all over the place so using this optical focus we can actually collect a lot of the bright spots and concentrate them onto this ultrasound focal spot if we were to use an your higher-order effect we catch you coalesce all of them into a single spot so this can be extremely powerful right


so you here's the signal by 6000 times it's a huge enhancement one more possibility of finding a guy star is to use motion right so when there's blood flow freaks for example the blood flow can be used to serve as a guy starts moving so we have this cartoon if you have a plane behind a child for example can we actually track that plane right so using the motion of the object as a guy star itself all right let me spend a couple more slides talk about one last technology we're working on in fact this paper up here today I knew actually this


our work made cover of the nature as we know this is the best scientific journal so we developed the technology that allows us to literally detect the fastest phenomenon possible right allowed by physics as we know Einstein's relativity theory says nothing can travel beyond the speed of light so we're detecting the light pulse itself and the light pulses are traveling in space at a speed of light we're capturing the light pulses as the light propagates in space get reflected by this mirror and if the my rate bends as


a crosses interface of two media you can see the angles will change right or you've had two pulses in two media and we can watch them a race and see which one will fly will travel faster and here you know what I saw a green pulse traveling here it'll excite some fluorescence and this red spot is actually a fluorescent light so we're watching this fluorescent light to decay and with a single laser shot we observed this phenomenon even the force and decay is on the nanosecond scale because we have picosecond resolution so that


nanosecond looks like eternity for us so this can be used for very high speed microscopy or you can potentially use this in combination with the Hubble telescope for example to look at very large phenomenon right like supernovae for example so this has very broad applications potentially and this is the technology we just developed I don't know how much detail we need to get into this maybe I should skip at this late hour you can ask me questions later if you're curious about this so I've covered a lot of different technologies


here started with the motivation and challenges in your field I talked about photoacoustic CT photo QC microscopy in two forms time reversal and what we call cup compressed ultra-fast photography Washington University requires me to discuss my financial financial interest with two companies which have commercialized the photo because it photoacoustic tomography and we're funded by NIH through various projects thank you very much I'll be happy to entertain any questions if there's any oh it's hard for me to see


so tissue imaging is the main goal for our research but you can potentially use it for some other applications even non biomedical right you can imagine robotic vision for underwater right so photo if there's turbidity what we call when there's a muddy water for example right you can't really see very far underwater so using photo acoustics so you can overcome the turbidity you fire some light pulses if your goal is to see a couple meters beyond you right so potentially like and propagate that for our generate acoustic waves then you can


pick them pick that up and form an image does that answer your question okay and there was yeah back there please so it hurt you a light-induced sound so what happens is light is first absorbed so you generate a transient heating a very short temperature rice right so on the order of nano second scale because we use nanosecond laser pulses and so that temperature rises as you can imagine is gonna cause thermo elastic expansion and that pushes tissue even though this is very my new every milli degree gives you eight millibars or 800


Pascal's of pressure rice which is already detectable so if you generate hundreds of million degrees temperature rise then you get a very bright signal to detect and that allows us to form a image so this is called a photo acoustic effect so basically it's a photo thermal and thermal acoustic in the end that we just call that photo acoustic affect the standard detectors has to be coupled acoustically to the tissue you can direct it touch it just like when you perform ultrasound imaging in the hospital they typically apply some gel


on the skin to to ensure acoustic coupling water coupling is one way gel coupling is more convenient for a lot of applications however our field is also developing non-contact sensing of acoustic waves through optical interferometry so if you shine light on to the tissue surface if there's vibration on the surface that displacement can be picked up through optical interferometry and that can be translated into acoustic wave as well so that's a potential non-contact version for now most of the implementations are


based on the contact version it's more traditional and it's better developed there's yeah please mm-hm so right now for breast cancer image in extra mammography is still the gold standard so we're still sticking with that one there are two types of directions that our field is taken one is to supplement extra mammography because x-ray mammography you know as since it's as sensitive as it is they have trouble with young women with reader graphically dense breast so where they really feel miserable the other flaw with x-ray mammography is the very


high false positive rate so that causes a lot of you know biopsies you know subsequent tests which turned out to be unnecessary eventually so can we use photo acoustics to supplement right if x-ray detects this as positive can we confirm if this is truly positive or not by detecting the functional information another way that's more takes longer it's going to take longer to validate is to star from breast cancer screening to begin with so can we use photoacoustic tomography to screen for breast cancer without using ionizing radiation at all


just start from from the functional contrast provided by photo acoustics the reason I said is going to take longer it's because even though breast cancer is a huge problem the rate of incidence is still relatively low you know you have to test like a thousand patients to get enough patients with breast cancer so you can establish the statistics so it's a more difficult problem any more questions yeah please all right images right yeah so it's a very good question your temp is still talking about photoacoustic tomography


right so there are two different ways of getting an image with the microscopy technique with a single laser shot you get a 1d image which is depth resolved so you eliminate along the vertical axis for example then you generally the essentially a volumetric acoustic source but then we use ultrasound transducer to pick up the signals so the acoustic time of rival is gonna tell you the depth information you get a 1d image with a single laser shot then you have to use scan linearly to get a 2d image then you have the if you want to get a 3d image


then you have the raster scan that's one way of getting an image 3d image another way is to use a ray of transducers so for example like the ringing array I showed right so we basically for the reign of 512 elements surrounding the head of animal or a body of animal or wherever we want an image like the breast then we use a broad field light illumination we don't focus light here at all we just light light photons basically bathe the tissue you generate the 3d volumetric source then your ring is going to detect signals from a slice


because we acoustically focus in the elevational direction the height direction and then we detect signal from the from this slice then we use image reconstruction to form a 2d image and if you want to get a third dimension of course you do the scan now this is a way the 1d array now if budget is not a problem then we can potentially get a 2d array I mean in the ideal world that you imagine we could surround the brass or the head with a lot of transducers in that case with a single laser shot you should be able to get a 3d image but


right now the the technology allows us to get a ring array or 1d array at a reasonable price but a two-dimensional array is I know quite expensive in fact the ultrasound world has been working on that for quite some time and they're talking about one happy in other words one dimensional density is high the second dimensional density is much lower because you simply cannot have that many transducers ultrasound transducers and still maintain the cost yeah please mm-hmm so I I was trained in laser physics so I got my PhD from rice and I my PhD thesis


was actually on my chemistry project after I got my PhD I decided to switch to something more applied so I worked for MD Anderson Cancer Center there was a laser lab I think that was a very good fit for my career goal so for applications in ori i think there are several potential applications so one of them is the cancer demarcation as I mentioned can we have a complete removal tumor so you minimize the recurrence rate another application as summation is the bring oxygen consumption monitoring we want to do that now you basically so


this is what's so good about Wash U right so even though most of my lab spaces in the hilltop or Danforth campus I have a lab in the medical school as well we have a lot of collaborators you know so physicians Wash U physicians are very eager to work with engineers they want to work with us the knock on my door come to my office want to work with engineers to apply our technology to their problems so we're targeting multiple problems it GI tract breast you know breast cancer staging melanoma you name it so we want to see the real


impact in the human side the photo acoustic tomography has been commercialized by several companies now I personally work with two of them so for preclinical imaging it has been you know established so there are products available they are being sold for a human imaging it's not there yet so I was not allowed to mention the name of the company which has licensed our IP for human imaging but so we're very happy that this is moving forward so it's going to take some time eventually I'd like to see this is this as a daily used at all


from the amazing results and vintage Atari games deep Minds victory with alphago stunning breakthroughs in robotic arm manipulation and even beating professional players at 1v1 dota the field of reinforcement learning has literally exploded in recent years ever since the impressive breakthrough on the imagenet classification challenge in 2012 the successes of supervised deep learning have continued to pile up and people from many different backgrounds have started using deep neural nets to solve a wide range of new tasks

An introduction to Reinforcement Learning


including how to learn intelligent behavior in complex dynamic environments so in this episode I will give a general introduction into the field of reinforcement learning as well as an overview of the most challenging problems that we're facing today if you're looking for a solid introduction into the field of deep reinforcement learning then this episode is exactly what you're looking for my name is Xander and welcome to archive insights [Laughter] [Music] [Music] so in its 2017 Peter Emil gave a very inspiring demo in front of a large


audience of some of the brightest minds in AI and machine learning so you showed this video where a robot is cleaning a living room bringing somebody a bottle of beer and basically doing a whole range of mundane tasks that robots in sci-fi movies can do without question and then at the end of the video peter revealed that the robots actions were actually entirely remote-controlled by a human operator and the takeaway from this demo I think is a very important one it basically says that the robots we've been building for decades now are


physically perfectly capable of doing a wide range of useful tasks but the problem is that we can't embed them with the needed intelligence to do those things so basically creating useful state-of-the-art robotics is a software challenge and not a hardware problem and so it turns out that having a robot learn how to do something very simple like picking up a bottle of beer can be a very challenging task and so in this video I want to introduce you guys to the whole subfield in machine learning that's called reinforcement learning


which i think is one of the most promising directions to actually get to very intelligent robotic behavior so in the most common machine learning applications people use what we call supervised learning and this means that you give an input to your neural network model but you know the output that your model should produce and therefore you can compute gradients using something like the back propagation algorithm to train that network to produce your outputs so imagine you want to train a neural network to play the game of pong what


you would do in a supervised setting is you would have a good human gamer play the game of pong for a couple of hours and you would create a data set where you log all of the frames that that human is seeing on the screen as well as the actions that he takes in response to those frames so whatever is pushing the up arrow or the down arrow and we can then feed those input frames through a very simple neural network that at the output can produce two simple actions it's either going to select the up action or the down action and by simply


training on the data set of the human gameplay using something like back propagation we can actually train that neural network to replicate the actions of the human gamer but there are two significant downsides to this approach so on the one hand if you want to do supervised learning you have to create a data set to train on which is not always a very easy thing to do and on the other hand if you train your neural network model to simply imitate the actions of the human player well then by definition your agent can never be better at


playing the game of pong than that human gamer for example if you want to train a neural net to be better at playing the game of gold and the best human then by definition we can't use supervised learning so is there a way to have an agent learn to play a game entirely by itself well fortunately there is and this is called reinforcement learning so the framework and reinforcement learning is actually surprisingly similar to the normal framework in supervised learning so we still have an input frame we run it through some neural network model and


the network produces an output action we either up or down but the only difference here is that now we don't actually know the target label so we don't know in any situation whether we should have gone up or down because we don't have a data set to train on and in reinforcement learning the network that transforms input frames to output actions is called the policy Network now one of the simplest ways to train a policy network is a method called policy gradients so the approach in policy gradients is that you


start out with a completely random network you feed that network a frame from the game engine it produces a random up with action you know either up or down you send that action back to the game engine and the game engine produces the next frame and this is how the loop continues and the network in this case it could be a fully connected network but you can obviously apply convolutions there as well and now in reality the output of your network is going to consist of two numbers the probability of going up and the probability of going


down and what you will do while training is actually sample from the distribution so that you're not always going to repeat the same exact actions and this will allow your agent to sort of explore the environment a bit randomly and hopefully discover better rewards and better behavior now importantly because we want to enable our agent to learn entirely by itself the only feedback that we're gonna give it is the scoreboard in the game so whenever our agent manages to score a goal it will receive a reward of +1 and if the


opponent scored a goal then our agent will receive a penalty of minus 1 and the entire goal of the agent is to optimize its policy to receive as much reward as possible so in order to train our policy network the first thing we're gonna do is collect a bunch of experience so you're just gonna run a whole bunch of those game frames through your network select random actions feed them back into the engine and just create a whole bunch of random pong games and now obviously since our agent hasn't learned anything useful yet it's


gonna lose most of those games but the thing is that sometimes our agent might get lucky sometimes it's going to randomly select a whole sequence of actions that actually lead to scoring a goal and in this case our agent is going to receive a reward and a key thing to understand is that for every episode regardless of whether we want a positive or a negative reward we can already compute the gradients that would make the actions that our agents has chosen more likely in the future and this is very crucial and so what policy


gradients are going to do is that for every episode where we've got a positive reward we're going to use the normal gradients to increase the probability of those actions in the future but whenever we got a negative we're gonna apply the same gradient but we're gonna multiply it with minus one and this minus sign will make sure that in the future all the actions that we took in a very bad episode are going to be less likely in the future and so the result is that while training our policy network the actions that lead to


negative rewards are slowly going to be filtered out and the actions that leads to positive rewards are going to become more and more likely so in a sense our agent is learning how to play the game of pong now I know this was a very quick introduction to reinforcement learning so if you want to read up a bit and spend a little bit more time in thinking about the details I really recommend to read and rake carpet these blog post pong from pixels it does a phenomenal job at explaining all the details all right so we can use


policy gradients to train a neural network to play the game of pong that's amazing right well yes it is but as always there are a few very significant downsides to using this methods let's go back to pong one more time so imagine that your agent has been training for a while and it's actually doing a pretty decent job at playing the game of pong it's bouncing the ball back and forth but then at the end of the episode it makes a mistake it lets the ball through and it gets a negative penalty so the problem with policy gradients is that


our policy gradient is going to assume that since we lost that episode all of the actions that we took there must be bad actions and is going to reduce the likelihood of taking those actions in the future but remember that actually the most part of that episode we were doing really well so we don't really want to decrease the likelihood of those actions and in reinforcement learning this is called the credit assignment problem it's where if you get a reward at the end of your episode well what are the exact actions that led to that specific


reward and this problem is entirely related to the fact that we have what we call a sparse reward setting so instead of getting a reward for every single action we only get a reward after an entire episode and our agent needs to figure out what part of its action sequence we're causing the reward that it eventually gets so in the case of punk for example our agent should learn that it's only the actions right before it hits the ball that are truly important everything else once the ball is flying off it doesn't really matter


for the eventual reward and so the result of this sparse reward setting is that in reinforcement learning algorithms are typically very sample inefficient which means that you have to give them a ton of training time before they can learn some useful behavior and I've made a previous video to compare the sample efficiency of reinforcement learning algorithms with human learning that goes much deeper into why this is the case and now it turns out that in some extreme cases the sparse reward setting actually fails completely so a


famous example is the game Montezuma's Revenge where the goal of the agent is to navigate a bunch of ladders jump over a skull grab a key and then actually navigate to the door - in order to get to the next level and the problem here is that by taking random actions your agent is never gonna see a single reward because you know the sequence of actions that it needs to take to get that reward is just too complicated it's never gonna get there with random actions and so your policy gradient is never gonna see a single positive reward so it has no


idea what to do in the same case applies to robotic control where for example you would like to train in robotic arm to pick up an object and stack it onto something else well the typical robot has about seven joints that it can move so it's a relatively high action space and if you only give it a positive reward when it's actually successfully stacked a block well by doing random exploration it's never gonna get to see any of that reward and I think it's important to compare this with the traditional supervised deep learning successes that


we get into something like computer vision for example so the reason computer vision works so well is that for every single input frame you have a target label and this lets you do very efficient gradient descent with something like back propagation whereas in a reinforcement learning setting you're having to deal with this very big problem of sparse reward setting and this is why you know computer vision is showing some very impressive results while something is simple as stacking one block onto another seems very difficult even for


state-of-the-art woodland [Music] and so the traditional approach to solve this issue of sparse rewards has been the use of rewards shaping so reward chipping is the process of manually designing a reward function that needs to guide your policy to some desired behavior so in the case of montezuma's revenge for example you could give your agent a reward every single time it manages to avoid the skull or reach the key and these extra rewards will guide your policy to some desired behavior and while this obviously makes it easier for


your policy to converge to desired behavior there are some significant downsides to reward shaping so firstly reward shaping is a custom process that needs to be redone for every new environment you want to train a policy so if you're looking at the benchmark of Atari for example well you would have to craft a new reward function for every single one of those games that's just not scalable the second problem is that we Ward shaping suffers from what we call the alignment problem so it turns out that reward shaping is actually


surprisingly difficult in a lot of cases when you when you shape your reward function your agent will find some very surprising way to make sure that it's getting a lot of reward but not doing at all what you wanted to do and in a sense the policy is just overfitting to that specific reward function that you designed while not generalizing to the intended behavior that you had in mind and there's a lot of funny cases where reward shaping goes terribly wrong so here for example the agent was trained to do jumping and the reward function


was the distance from its feet to the ground and what this agent has learned is to simply grow a very tall body and do some kind of a backflip to make sure that its feet are very far from the ground to give you one final idea of how hard it can be to the reward shaping I mean look at this shaped reward function for a robotic control task I don't even want to know how long the people from this paper spent on designing this specific reward function to get the behavior that they wanted and finally in some cases like alphago for example by


definition you don't want to do any reward shaping because this will constrain your policy to the behavior of humans which is not exactly optimal in every situation so the situation that we're in right now is that we know that it's really hard to train in a sparsely setting but at the same time it's also very tricky to shape a reward function and we don't always want to do that and to end this video I would like to note that a lot of media stories picture reinforcement learning as some kind of a magical AI sauce that lets the agent


learn on itself or improve upon its previous version but the reality is that most of these breakthroughs are actually the work of some of the brightest minds alive today and there's a lot of very hard engineering going on behind the scenes so I think that one of the biggest challenges in navigating our digital landscape is discerning truth from fiction in this ocean of clickbait that is powered by the advertisement industry and I think the Atlas robot from Boston Dynamics is a very clear example of what I mean so I think if you


go out on the streets and you ask a thousand people with the most advanced robots today are well they would probably point to Atlas from Boston Dynamics because everybody has seen the video where it does a backflip but the reality is that if you think about what's what Boston Dynamics is actually doing well it's very likely that there's not a lot of deep learning going on there if you look at their previous papers in the research track record well they're they're doing a lot of very advanced robotics don't get me wrong but


there's not a lot of self driven behavior there's not a lot of intelligent decision-making going on in those robots so don't get me wrong Boston Dynamics is a very impressive robotics company but the media images they've created might be a little bit confusing to a lot of people that don't know what's going on behind the scenes but nonetheless if you look at the progress of research that is going on I think we should not be negligible of the potential risks that these technologies can bring so I think it's very good that


a lot more people are getting involved in the whole a AI safety research because this is going to become very fundamental threats like autonomous weapons and mass surveillance are to be taken very seriously and so the only hope we have is that international law is going to be somewhat able to keep up with the rapid progress we see in technology but on the other hand I also feel like the media is focusing way too much on the negative side of these technologies simply because people fear what they don't understand and well fear


sells more advertisement than utopias so I personally believe that most if not all technological progress is beneficial in the long run as long as we can make sure that there are no monopolies that can maintain or enforce their power with the malignant use of AI well anyway enough politics for one video so this video was an introduction into deep reinforcement learning and an overview of the most challenging problems that we're facing in the field in the next video I will dive into some of the most recent approaches that try to tackle these


problems of sample efficiency and the sparse reward setting so specifically I will cover a few technical papers dealing with approaches like auxilary or reward settings intrinsic curiosity hindsight experience replay and so on I've also seen that a few people have chosen to support me on patreon for which I would just like to say thank you very much I mean it really means a big deal to me I'm doing these videos completely in my spare time and knowing that there's people out there that appreciate this content really feels


let me introduce you to mrs. mani she came to the emergency room she searched his fifty two-years-old she came to the emergency room with a foot sore doctors investigated of with saw and she ended up staying there in the hospital for 22 days here's what happened when she came to the emergency room for a foot sore they inspected her they saw no real reason for medical concern but they wanted to monitor in case her foot sore was infected so they put her in the general ward on day three she starts developing symptoms of what looks like

Better Medicine Through Machine Learning | Suchi Saria | TEDxBoston