Anders Ynnerman: 医学数据可视化

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http://dotsub.com/view/9b65512b-7305-4ce9-9a4b-2418429f60ba
Anders Ynnerman: 医学数据可视化
我首先给大家展示一个难题， 一个处理数据的难题， 处理这些 医学数据的难题。 这对我们来说真的是个很大的挑战。 这就是让我们头疼的大难题。 这是一台计算机X射线断层扫描仪-- 也就是CT机。 这个是很棒的机器。 它使用X射线，X光束， 从四面对人体进行快速扫射。 通过这台机器的时间约为30秒， 之后，它能收集到 海量的信息。 从提高医疗质量的角度看， 这台机器 真是绝了。 但是，它也同时给我们出了个难题。 这个难题就在这张照片里。 我们现在面临着 医学数据爆炸的难题。 这个难题就摆在我们面前。 我们来回顾一下历史。
我们回到几年以前，看看当时的情况。 这些机器 从二十世纪七十年代开始被投入使用-- 它们能够对人体进行扫描， 拍出100多张 人体的透视图。 恕我冒昧，为了让大家看得更明白， 我把这些数据转化成通俗的比方。 这些数据总共有大约50兆， 这不算大， 我们今天用普通移动设备处理的信息 要比这大得多。 如果你把这些数据转化成电话簿， 那么你会得到高达一米的一堆电话簿。 再看看我们今天 所使用的这些机器， 我们可以在短短几秒钟内 得到24000张人体透视图。 这相当于20千兆的数据， 或800本电话簿。 这些电话簿堆起来足有200米高。 接下来会发生什么呢-- 我们所看到的，是一个开始-- 一种技术的发展趋势， 我们开始考虑耗时的问题。 我们甚至可以捕捉人体的动态。 试想一下， 我们在5秒钟内收集的数据， 大小为一百万兆。 那相当于八十万本书 或一万六千米厚的电话簿。 这只是从一个患者身上采集的一组数据。 这就是我们面临的难题。
一个巨大的挑战。 这里有两万五千个图像， 试想一下， 在过去，放射线专家是这样工作的。 那么今天，他们就得把两万五千张图放上去， 这样一张张地看：“第两万五千张，好了好了， 找到问题了。” 现在他们可不能这么做了；这是不可能的。 那么我们就必须使一点小聪明。 我们把这些图片整合在一起。 假设你把自己从各个角度切成簿片， 接着，再把这些簿片拼回去， 组成一个数据堆，再组成一个数据块。 这就是我们的工作。 我们把这千兆或百万兆的数据整合成这个数据块。 当然，这个数据块 只包含了被人体吸收了的 X光所呈现出的人体各个部位。 我们需要的是，找出一种方法 让我们看到，我们想要看到的部位， 同时把那些我们不需要看到的部分隐藏起来。 把数据转化为 这样的形式。 这是颇具挑战的。 而且是个艰巨的挑战。
使用计算机虽然能够更快更好地得到数据， 但是在得到几千兆 甚至上百万兆的数据之后 如何从中抽取有用信息，成了巨大的挑战。 我想透视心脏， 透视那些血管，肝脏， 在某些情况下， 我要看是否有肿瘤。 这时这个小宝贝给了我启示。 这是我女儿。 照片上是早上九点。 她正在玩电脑游戏。 她才两岁。 看她玩得眉飞色舞的。 她就是图形处理器 得到发展的原动力。 只要孩子们继续玩电脑游戏， 电脑制图的技术就会越来越好。 所以请大家回去以后多多鼓励自己的孩子打电脑游戏， 这对我帮助太大了。
这台机器 帮助我 分析医学数据。 我所利用的就是这些神奇的小设备。 时间倒退 到大概十年以前， 我得到赞助， 购买了第一台绘图电脑。 它是台巨大的机器， 由许多处理器，存储器等等组成的大柜子。 这台机器花了我一百万美元。 这台机器运算的速度跟我的iPhone差不多。 每个月都有新的显卡上市。 这是商家最新推出的产品-- 英伟达（NVIDIA），冶天（ATI），还有因特尔的产品也出来了。 花个几百美元， 你就能把这些东西买到手，装到自己电脑上， 这些显卡能完成许多不可思议的事情。 这就是 我们控制医疗数据爆炸的法宝， 再加上一些 绝妙的演算-- 精简数据， 提取研究用的相关数据。
接下来我会为大家展示我们的工作成果。 这是一组由CT机采集的数据。 这是一组完整的数据。 这是一位女性。你们能看到她的发丝。 还能看到她各个部位的结构。 你们可以看到她的牙齿以及里面的金属 在X光效果下的成像。 那是人造的部分。 但是通过使用， 装有标准显卡的普通电脑， 我就可以装入一个剪切平面软件。 所有的数据都在里面， 我可以进行翻转，从不同角度观察， 可以看到这位女性的问题是在哪里。 她的大脑有一处出血， 医生用一个支架对其进行修复， 那是一个金属钳锁紧了那根血管。 有了调节功能， 我就能自由决定哪些部分可以被隐去， 哪些部位可以凸显出来。 我可以看到头骨的结构， 好的，这位女性曾经做过开颅手术， 他们是从这个部位进去的。 这些都是非常精密的视图， 分辨率极高， 让我们看到了 现今标准显卡的真正能耐。
我们很好地利用了这个技术， 把大量的数据 压缩到这个系统里。 这是我们正在研究的应用之一-- 这在世界范围内引起了不小的轰动-- 这就是模拟验尸技术。 看着这庞大的数据群， 你们刚才看到我们能做全身扫描。 我们只要让整个人体通过CT机， 不到几秒钟，我们就能得到全身的数据。 这就是一次虚拟验尸。 你们可以看到我正在一层一层把画面剥开。 首先你看到的是包着裹尸袋的尸体， 接着，我把皮肤剥开-- 你们可以看见肌肉-- 最后你们可以看见这位女性的骨骼。
现在，我想强调一下， 对以下图片中的死者， 我深怀敬意-- 我将向大家展示几个模拟验尸的案例-- 我向这些因暴力导致死亡的人们 表示敬意 我展示的是他们的验尸情况。 在法医鉴定的案例中-- 在这几年里 在瑞典，我所在的地区 已经有大约400个案例 使用了 模拟验尸技术。 这是验尸的常规程序。 警察会决定-- 案发当晚， 他们会决定，好，我们需要对这个案子进行尸检。 于是第二天早上，大概六七点钟， 尸体就会被放进裹尸袋 运到我们中心 然后穿过CT机。 接着，放射线专家会，病理学家 有时候还需要法医， 一起进行观察数据， 他们会进行综合分析。 之后，他们决定在实际的尸检过程中应该如何操作。
现在我们看一些案例， 这是我们第一批案例的其中之一。 你们可以看到数据群的细节； 清晰度非常高。 我们采用的演算法 让我们可以把细节放大。 它完全受你控制， 你可以翻转，在这些设备上 进行实时观察。 案情就不多说了， 这是一起交通意外， 一个司机酒后驾车撞倒了一位女士。 我们可以很清晰地看到她骨头所受的损伤。 颈骨断裂导致死亡。 这位女士被车轮碾压， 所以她的颈部 受到了严重损伤。
这是另一个案例，受害人被刀刺死。 这也展示了我们的技术。 我们能够轻易地让人体内的人造金属物体 显现出来。 大家可以看到死者牙齿里的人造物-- 实际上是补牙的填充物-- 我设定了显示金属的功能， 所以身体其它部位都变得透明了。 这是另外一宗暴力案件。这一处不是致命伤。 致命的几刀捅进了心脏， 凶手最后 把刀插进死者一只眼球里。 这是另一个案子。 研究刀伤 是很有意思的。 大家可以看到那把刀穿过了心脏。 我们可以很清楚地看到 空气从一头穿进另一头， 这在实地的常规标准尸检中是很难看到的。 在刑事案件的侦察中， 这对确定死者死因 帮助非常大， 在一些案件中，还能协助案件调查， 找到凶手。
这里还有一个很有意思的案例。 你们看那颗子弹， 它射在这人的脊椎骨上。 我们所做的是，把这颗子弹，处理成一个光源， 这样子弹是发光的， 这样便于我们找到这些碎片。 在进行肉体解剖时， 想要翻遍身体各个部位去寻找那些碎片， 是非常困难的。
今天我非常高兴，能够想大家展示 这样一个设备， 那就是我们的模拟尸检台。 我们根据前期的演算法，使用图形处理器 开发出了这个触控设备。 这就是这台仪器， 让大家看看它大致的样子。 它使用起来就像一个巨型iPhone手机。 你可以在这台仪器上 做任何的动作， 你可以把它看成一个巨大的触屏。 如果你在考虑买一个iPad平板电脑， 赶紧打住；这才是你真正想要的。 史蒂夫（苹果公司CEO），你可听好啦。 这才是个非常实用的小仪器。 如果有机会，你一定要试试。 这手感可是一流的。 它引起了不小的轰动，我们也在努力推广这个技术， 努力把它运用在教学当中， 但是，也许在将来， 我们会更多地将它运用在临床医学上。 你可以从YouTube网上下载这个视频， 如果你有意，可以把模拟尸检的信息 介绍给其他人。
好的，既然我们谈到了“手感”， 那我就让大家看看一些真正有“手感”的数据。 目前这还只能算是科学幻想， 因为我们现在要去到未来。 现在的医生还没有开始使用这些技术， 但是我希望他们未来可以用上。 大家看到屏幕左边的是一个触控装置。 这是一支机械笔， 在这支笔里装有非常灵敏的监视器。 我可以用它触发力反馈。 当我触碰模拟数据时， 这支笔会发出反作用力，于是我得到了反馈。 我们看一下这个案例， 这是一个活人的扫描数据。 我拿着这支笔，看着数据， 把笔伸进他的头部， 突然间，我感到了反作用力， 我能触到皮肤， 如果再用点力， 就能穿过皮肤， 感觉到里面的骨骼。 再用点力，就穿过了骨骼， 从耳部附近插进去，这里的骨头很软。 现在我触碰到大脑了，感觉挺粘稠的。
这技术真是绝了。 更绝的还在后面，这是一颗心脏。 这些新型扫描仪真是太棒了， 仅在0.3秒之内 我就能把这整颗心脏扫描下来， 仪器的时间分辨率非常高。 请大家看这颗心脏， 我播放一段录像。 这是克里万，我的一个研究生， 他正在研究这个项目。 他正在操作触感仪器，也就是力反馈系统， 他正在用笔触碰这颗心脏， 这颗心正在他面前跳动， 他可以清楚地看到心脏跳动的情况。 他拿着笔，靠近心脏， 他正在拿笔触碰心脏， 这样，他可以感觉到一个患者活生生的心跳。 然后他可以检查心脏的动态。 他还可以进入心脏， 感觉里面瓣膜的动态。 我认为这就是心脏外科手术。 我是说这能让外科医生做梦都偷笑， 因为你可以在动手术之前 先进入患者的心脏， 进行一次高清画质的模拟手术。 这真是太美妙了。
现在我们看到的科幻技术更加超前。 大家应该听说过功能性核磁共振成像技术。 这是一个很有意思的项目。 核磁共振成像被运用磁场， 电波频率 对大脑或身体其它部位进行扫描。 我们在用这个技术 获取大脑结构的信息， 不仅如此，我们还能测量 血液在含氧以及缺氧的状态下， 其磁属性的变化差异。 这意味着我们有可能 将大脑活动的情况反映出来。 这是我们目前正在研发的项目。 现在大家看到的是研发工程师马茨 他正在通过核磁共振成像系统， 他戴着眼镜。 从眼镜里他可以看到图像。 当他在受扫描的时候，我可以给他展示图像。 这有点吓人， 因为马茨看到的是这个， 他自己的大脑。 马茨正在使用大脑的这个部分。 可能他正在用右手做这个动作， 因为他的左脑的运动皮层 正在兴奋。 他可以看到同样的图像。 这些成像技术都是最新的。 我们在这方面的研究已经进行了很长一段时间。
这是马茨大脑的另外一次活动。 我们让马茨从100开始倒数。 于是他开始“100， 97， 94” 这样倒数。 大家可以看到这个处理数学的指令让他的大脑工作， 让整个大脑都活跃起来了。 这绝了。我们能够进行实时操作。 我们可以进行测试。我们可以给他下指令。 大家还可以看到他的视觉皮层 在他后脑的部位兴奋起来了。 这是因为他在看自己的大脑。 他同时 也在听我们的指示。 尽管信号处在大脑的深层部位， 但是它活跃部位可以显现出来， 这是因为所有的数据都在其中了。 一会儿大家会看到-- 就是这里。 马茨，现在动一动你的左脚。 接着他开始动左脚。 持续了20秒钟。 忽然，这个部位活跃了起来。 这样我们看到这里的皮层运动区兴奋起来。 这真的非常神奇。 我认为这是个绝妙的工具。 结合我之前提到的内容， 我们可以利用这样的工具 去真正了解 神经元和大脑是如何工作的， 我们的技术可以做出非常高的画质 和极快的分辨率。
现在我们在中心的工作变得很有意思了。 这是一台计算机辅助断层扫“猫”仪（CAT）-- 这是一头狮子 来自诺尔雪平当地的一家动物园。 她被送到中心， 注射了镇定剂， 接着被放进这台扫描仪里。 接着，我得到了这头狮子的全套数据。 我能得出画质非常高的图像。 我可以把这头狮子层层剥开。 可以看到她身体内部的情况。 我们一直在做这方面的实验。 我觉得在将来 会是非常有用的技术， 因为我们对动物解剖学知之甚少。 兽医们所得到的信息不够深入了。 我们可以对任何东西， 任何动物进行扫描。 唯一的缺点是体积问题。 这是一头熊。 把它弄进这台机器可真不容易。 这头熊非常憨态可掬，也很友好。 大家看，这是熊的鼻子。 你可能很想摸摸它， 但是当你改变效果，再看， 就得小心了。
至此， 我想要感谢 所有帮助我做出这些图像的人们。 这是许多人的辛劳换来的， 他们收集数据，进行演算， 编写软件。 感谢这些才华洋溢的工作人员。 我的人生信条是：我只雇用比我精明的人。 以上这些人大多都比我聪明。
非常感谢大家。
（众人鼓掌）
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Anders Ynnerman: Visualizing the medical data
I will start by posing a little bit of a challenge, the challenge of dealing with data, data that we have to deal with in medical situations. It's really a huge challenge for us. And this is our beast of burden. This is a computer tomography machine -- a CT machine. It's a fantastic device. It uses X-rays, X-ray beams, that are rotating very fast around the human body. It takes about 30 seconds to go through the whole machine and is generating enormous amounts of information that comes out of the machine. So this is a fantastic machine that we can use for improving health care. But as I said, it's also a challenge for us. And the challenge is really found in this picture here. It's the medical data explosion that we're having right now. We're facing this problem. And let me step back in time.
Let's go back a few years in time and see what happened back then. These machines that came out -- they started coming in the 1970s -- they would scan human bodies, and they would generate about 100 images of the human body. And I've taken the liberty, just for clarity, to translate that to data slices. That would correspond to about 50 MB of data, which is small when you think about the data we can handle today just on normal mobile devices. If you translate that to phone books, it's about one meter of phone books in the pile. Looking at what we're doing today with these machines that we have, we can, just in a few seconds, get 24,000 images out of a body. And that would correspond to about 20 GB of data, or 800 phone books. And the pile would then be 200 meters of phone books. What's about to happen -- and we're seeing this, it's beginning -- a technology trend that's happening right now is that we're starting to look at time result situations as well. So we're getting the dynamics out of the body as well. And just assume that we will be collecting data during five seconds, and that would correspond to one terabyte of data. That's 800,000 books and 16 km of phone books. That's one patient, one data set. And this is what we have to deal with.
So this is really the enormous challenge that we have. And already today -- this is 25,000 images. Imagine the days when we had radiologists doing this. They would put up 25,000 images, they would go like this, "25,0000, okay, okay. There is the problem." They can't do that anymore; that's impossible. So we have to do something that's a little bit more intelligent than doing this. So what we do is we put all these slices together. Imagine that you slice your body in all these directions, and then you try to put the slices back together again into a pile of data, into a block of data. So this is really what we're doing. So this gigabyte or terabyte of data, we're putting it into this block. But of course, the block of data just contains the amount of X-ray that's been absorbed in each point in the human body. So what we need to do is to figure out a way of looking at the things we do want to look at and make things transparent that we don't want to look at. So transforming the data set into something that looks like this. And this is a challenge. This is a huge challenge for us to do that.
Using computers, even though they're getting faster and better all the time, it's a challenge to deal with gigabytes of data, terabytes of data and extracting the relevant information. I want to look at the heart, I want to look at the blood vessels, I want to look at the liver, maybe even find a tumor in some cases. So this is where this little dear comes into play. This is my daughter. This is as of 9:00 am this morning. She's playing a computer game. She's only two years old, and she's having a blast. So she's really the driving force behind the development of graphics processing units. As long as kids are playing computer games, graphics is getting better and better and better. So please go back home, tell your kids to play more games, because that's what I need.
So what's inside of this machine is what enables me to do the things that I'm doing with the medical data. So really what I'm doing is using these fantastic little devices. And you know, going back maybe 10 years in time when I got the funding to buy my first graphics computer. It was a huge machine. It was cabinets of processors and storage and everything. I paid about one million dollars for that machine. That machine is, today, about as fast as my iPhone. So every month there are new graphics cards coming out. And here is a few of the latest ones from the vendors -- NVIDIA, ATI, Intel is out there as well. And you know, for a few hundred bucks you can get these things and put them into your computer, and you can do fantastic things with these graphics cards. So this is really what's enabling us to deal with the explosion of data in medicine, together with some really nifty work in terms of algorithms -- compressing data, extracting the relevant information that people are doing research on.
So I'm going to show you a few examples of what we can do. This is a data set that was captured using a CT scanner. You can see that this is a full data. It's a woman. You can see the hair. You can see the individual structures of the woman. You can see that there is scattering of X-rays on the teeth, the metal in the teeth. That's where those artifacts are coming from. But fully interactively on standard graphics cards on a normal computer, I can just put in a clip plane. And of course all the data is inside, so I can start rotating, I can look at it from different angles, and I can see that this woman had a problem. She had a bleeding up in the brain, and that's been fixed with a little stent, a metal clamp that's tightening up the vessel. And just by changing the functions, then I can decide what's going to be transparent and what's going to be visible. I can look at the skull structure, and I can see that, okay, this is where they opened up the skull on this woman, and that's where they went in. So these are fantastic images. They're really high resolution, and they're really showing us what we can do with standard graphics cards today.
Now we have really made use of this, and we have tried to squeeze a lot of data into the system. And one of the applications that we've been working on -- and this is gotten a little bit of traction worldwide -- is the application of virtual autopsies. So again, looking at very, very large data sets, and you saw those full-body scans that we can do. We're just pushing the body through the whole CT scanner, and just in a few seconds we can get a full-body data set. So this is from a virtual autopsy. And you can see how I'm gradually peeling off. First you saw the body bag that the body came in, then I'm peeling off the skin -- you can see the muscles -- and eventually you can see the bone structure of this woman.
Now at this point, I would also like to emphasize that, with the greatest respect for the people that I'm now going to show -- I'm going to show you a few cases of virtual autopsies -- so it's with great respect for the people that have died under violent circumstances that I'm showing these pictures to you. In the forensic case -- and this is something that there's been approximately 400 cases so far just in the part of Sweden that I come from that has been undergoing virtual autopsies in the past four years. So this will be the typical work-flow situation. The police will decide -- in the evening, when there's a case coming in -- they will decide, okay, is this a case where we need to do an autopsy. So in the morning, in between six and seven in the morning, the body is then transported inside the body bag to our center and is being scanned through one the the CT scanners. And then the radiologist, together with the pathologist and sometimes the forensic scientist, looks at the data that's coming out, and they have a joint session. And then they decide what to do in the real physical autopsy after that.
Now looking at a few cases, here's one of the first cases that we had. You can really see the details of the data set; it's very high-resolution. And it's our algorithms that allow us to zoom in on all the details. And again, it's fully interactive, so you can rotate and you can look at things in real time on these systems here. Without saying too much about this case, this is a traffic accident, a drunk driver hit a woman. And it's very, very easy to see the damages on the bone structure. And the cause of death is the broken neck. And this women also ended up under the car, so she's quite badly beaten up by this injury.
Here's another case, a knifing. And this is also again showing us what we can do. It's very easy to look at metal artifacts that we can show inside of the body. You can also see some of the artifacts from the teeth -- that's actually the filling of the teeth -- but because I've set the functions to show me metal and make everything else transparent. Here's another violent case. This really didn't kill the person. The person was killed by stabs in the heart, but they just deposited the knife by putting it through one of the eyeballs. Here's another case. It's very interesting for us to be able to look at things like knife stabbings. Here you can see that knife went through the heart. It's very easy to see how air has been leaking from one part to another part, which is difficult to do in a normal, standard, physical autopsy. So it really, really helps the criminal investigation to establish the cause of death, and in some cases also directing the investigation in the right direction to find out who the killer really was.
Here's another case that I think is interesting. Here you can see a bullet that has lodged just next to the spine on this person. And what we've done is that we've turned the bullet into a light source, so that bullet is actually shining, and it makes it really easy to find these fragments. During a physical autopsy, if you actually have to dig through the body to find these fragments, that's actually quite hard to do.
One of the things that I'm really, really happy to be able to show you here today is our virtual autopsy table. It's a touch device that we have developed based on these algorithms, using standard graphics GPU's. It actually looks like this, just to give you a feeling for what it looks like. It really just works like a huge iPhone. So we've implemented all the gestures you can do on the table, and you can think of it as an enormous touch interface. So if you were thinking of buying an iPad, forget about it; this is what you want instead. Steve, I hope you're listening to this, all right. So it's a very nice little device. So if you have the opportunity, please try it out. It's really a hands-on experience. So it's gained some traction, and we're trying to roll this out and trying to use it for educational purposes, but also, perhaps in the future, in a more clinical situation. There's a YouTube that you can download and look at this, if you want to convey the information to other people about virtual autopsies.
Okay, now that we're talking about touch, let me move on to really touching data. And this is a bit of science fiction now, so we're moving into really the future. This is not really what the medical doctors are using right now, but I hope they will in the future. So what you're seeing on the left is a touch device. It's a little mechanical pen that has very, very fast [unclear] monitors inside of the pen. And so I can generate a force feedback. So when I virtually touch data, it will generate touch forces in the pen, so I get a feedback. So in this particular situation, it's a scan of a living person. I have this pen, and I look at the data, and I move the pen towards the head, and all of a sudden I feel resistance. So I can feel the skin. If I push a little bit harder, I'll go through the skin, and I can feel the bone structure inside. If I push even harder, I'll go through the bone structure, especially close to the ear where the bone is very soft. And then I can feel the brain inside, and this will be the slushy like this.
So this is really nice. And to take that even further, this is a heart. And this is also due to these fantastic new scanners, that just in 0.3 seconds, I can scan the whole heart, and I can do that with time resolution. So just looking at this heart, I can play back a video here. And this is Karljohan, one of my graduate students who's been working on this project. And he's sitting there in front of the Haptic device, the force feedback system, and he's moving his pen towards the heart, and the heart is now beating in front of him, so he can see how the heart is beating. He's taken the pen, and he's moving it towards the heart, and he's putting it on the heart, and then he feels the heartbeats from the real living patient. Then he can examine how the heart is moving. He can go inside, push inside of the heart, and really feel how the valves are moving. And this, I think, is really the future for heart surgeons. I mean it's probably the wet dream for a heart surgeon to be able to go inside of the patient's heart before you actually do surgery, and do that with high-quality resolution data. So this is really neat.
Now we're going even further into science fiction. And we heard a little bit about functional MRI. Now this is really an interesting project. MRI is using magnetic fields and radio frequencies to scan the brain, or any part of the body. So what we're really getting out of this is information of the structure of the brain, but we can also measure the difference in magnetic properties of blood that's oxygenated and blood that's depleted of oxygen. That means that it's possible to map out the activity of the brain. So this is something that we've been working on. And you just saw Motts the research engineer there going into the MRI system, and he was wearing goggles. So he could actually see things in the goggles. So I could present things to him while he's in the scanner. And this is a little bit freaky, because what Motts is seeing is actually this. He's seeing his own brain. So Motts is doing something here. And probably he is going like this with his right hand, because the left side is activated on the motor cortex. And then he can see that at the same time. These visualizations are brand new. And this is something that we've been researching for a little while.
This is another sequence of Motts' brain. And here we asked Motts to calculate backwards from 100. So he's going "100, 97, 94." And then he's going backwards. And you can see how the little math processor is working up here in his brain and is lighting up the whole brain. Well this is fantastic. We can do this in real time. We can investigate things. We can tell him to do things. You can also see that his visual cortex is activated in the back of the head, because that's where he's seeing, he's seeing his own brain. And he's also hearing our instructions when we tell him to do things. The signal is really deep inside of the brain as well, but it's shining through, because all of the data is inside this volume. And in just a second here you will see -- Okay, here. Motts, now move your left foot. So he's going like this. For 20 seconds he's going like that, and all of a sudden it lights up up here. So we've got motor cortex activation up there. So this is really, really nice. And I think this is a great tool. And connecting also with the previous talk here, this is something that we could use as a tool to really understand how the neurons are working, how the brain is working, and we can do this with very, very high visual quality and very fast resolution.
Now we're also having a bit of fun at the center. So this is a CAT scan -- computer aided tomography. So this is a lion from the local zoo outside of Norrkoping in Kolmarden, Elsa. So she came to the center, and they sedated her and then put her straight into the scanner. And then, of course, I get the whole data set from the lion. And I can do very nice images like this. I can peel off the layer of the lion. I can look inside of it. And we've been experimenting with this. And I think this is a great application for the future of this technology. Because there's very little known about the animal anatomy. What's known out there for veterinarians is kind of basic information. We can scan all sorts of things, all sorts of animals. The only problem is to fit it into the machine. So here's a bear. It was kind of hard to get it in. And the bear is a cuddly, friendly animal. And here it is. Here is the nose of the bear. And you might want to cuddle this one, until you change the functions and look at this. So be aware of the bear.
So with that, I'd like to thank all the people that have helped me to generate these images. It's a huge effort that goes into doing this, gathering the data and developing the algorithms, writing all the software. So, some very talented people. My motto is always, I only hire people that are smarter than I am and most of these are smarter than I am.
So thank you very much.
(Applause)