[Automatic captions by Autotekst using OpenAI Whisper V3. May contain recognition errors.] My name is Håvard Haugen and I come from the department of biomaterials at the faculty of odontology.
I am making this presentation together with my colleague Libert.
What we are researching is the reserves for the body.
For those of you sitting on the first row, you can see that I have a very long arch along my arm.
It was when I climbed on the roof and fell down and got the ladder over me.
And then I got 25 titanium screws and four plates in my hand here.
And then it is a very important tool for the doctors to see how well the screws and plates are sitting here.
That is to use the wrench.
And that's something we've researched a lot with.
The problem is that when you take a regular x-ray picture, you don't get a full picture.
So when I take a x-ray picture, it is very important for us to know which material fits well in the leg, and that it can be done in 3D.
And that's something we work a lot with.
As you can see, it's not my hand, but it's a tooth implant in an animal.
What I'm wondering about is how well the titanium screw sits in the leg, and has it managed to get the leg directly on the titanium screw?
And we can manage to find that out with the machines we have.
Then I can analyze where the leg is, where the screw is, and how much leg I can get on the screw.
Then I can analyze, as you can see in this area, there I have a little bit of leg that is missing, but most of the time I have good contact.
So this is a screw that is well integrated in the leg, and that is something that is extremely important for us to see.
The advantage of this is that it's not destructive.
I don't have to cut up my arm to look inside.
I can just look at the outside.
These screws and plates are in my hands.
But it's not just that that's important for my hands.
Because for my hands to work, it's not enough that just my legs are stable.
It's also important to know about the scenes and muscles and everything around.
I have just taken an example from an animal.
We have developed techniques where we can both see legs, skin and muscles at the same time.
Here you can see the forelimbs of a mouse.
We can see both skin and hair, together with the legs.
This must have an interaction effect.
Then we can get 3D models based on that.
Now we've got such an advanced method that we can even see cell and collagen structures in here, so we can go even more specifically into the system.
And then just a little before I got the message to give a little introduction.
First, what are we really doing?
How can we make such a type of picture?
Should I have a pointer?
Maybe I'll just show you.
This is the x-ray source, as you can see in the beginning.
There's a sample in the middle, and a detector.
And the samples go around.
If you're in a clinic, it's not my hand that goes around when I take a CB-CT, but the detector and the x-ray source that goes around.
We call that a cone beam CT.
It's like a cone that goes around.
In the machine we have here, it's the sample that rotates, and then the kidney source and the detector are attached.
So what separates them is how much I can see.
So if I go to the clinic in Luisenberg and look at my hand, I can't see in the resolution that I have on my hand.
lab for me and Libert.
Because this is typically up to 100 micrometers.
The best is maybe 50 micrometers.
While we can push down to the nano level.
And then we can get much better details.
And then we can tell a lot more about, not just that my leg is in good shape, but I can tell if my leg is healthy or not healthy.
where the leg grows, in which direction the leg goes, we get much more definition of the structure.
The fact that this technique is not destructive means that we can use it for many other things.
We don't need to destroy the object to analyze it.
So we do a lot of research, a lot of industrial research, and we see everything from food that is used in the salmon production to tablets produced in pharmacology.
We look at root fillings that are made in the clinic, how well they are made.
We look at geological materials, on insects, for example.
We look at meteorites.
We can even look at a project we did with biology on fish, where we saw the calcification of fish, where there was an area with a lot of birds, versus an area without birds, how much energy the fish used to develop the force mechanism in evolution.
So we use it for many different things.
At the university we also have two very nice instruments, both a micro and a nano set, and we also have a pretty good machine at the Natural History Museum.
We use it both in research and education, and we also use it for very well analyzed measurements.
But what are the challenges with our system?
Yes, there are a lot of challenges.
If you look at the flow of work in how the tests are done, and then the tests are put in the middle of this sample stage that rotates, then we start the ranking source, and then it shoots through, and then the picture is taken on the other side.
This produces an enormous amount of data.
Every time I go around, I get a new image.
If the resolution is very high, it generates very heavy amounts of data.
I have another problem.
If this is the short one that goes around, the one in the middle would get more light than the one on the outside.
Here I have a very high beam of light, but on the outside it is smaller.
All the horizontal plans I have, I have to process and calculate for the extra beam that comes in the middle.
It can be for reconstruction.
It requires a lot of data power.
If I have large data sets, it requires a lot of data power to reconstruct.
It can take a long time.
It's both a lot of CPU and a lot of GPU.
When I'm done, I've made vertical stacks.
I have a heavy data set.
Now I'm going to start analyzing my data.
If I have a heavy dataset, I need a very powerful computer to analyze the large data files.
It can take a long time.
One thing is to set up and scan the data and make sure that the sample is strong enough.
If the resolution is extremely high, there will be very little movement to make the sample worse.
So it takes a lot of time to set up everything and do all the scanning.
And then it takes a long time to do the reconstruction, and then you have to do the analysis.
And then we have another problem, that many of the software that we use to do such an advanced analysis is terribly expensive.
It costs up to 100,000 kroner a year.
If we have researchers who come in and say they're going to use this for two or three weeks,
then we can't expect them to pay such high costs for just that use.
So that's a bit of a hurdle for us, that we have heavy data, a lot of data power for reconstruction, heavy files that we want to reconstruct, and we have to analyze the data in due time, and can use terribly long time on analysis, plus that we have very expensive software that we have to use, and that is linked to one data machine.
And then we have users from all over the world who come with us.
They may only live in Råby in Oslo for two weeks.
They have a lot of tests and want to scan everything.
And then they don't have enough time to analyze their tests, and they don't have enough time to access the software we have.
Then we suddenly have a lot of data lying around that we don't get to use.
So what are we going to do then?
And this came up to
the development of this project that we have been working on with UCI.
We want to try to make an access to these data machines, so that we avoid the fact that we have a huge data machine, so we stand next to a machine, and that you can access it physically, but that we can also access it virtually.
No matter what you are in the world, you can access the data,
And that you can do the analysis.
Scanning is of course possible, but you can just come to us, scan, and then go back and do all the reconstruction and analysis in another place.
And without needing a very powerful computer that is just linked to a physical place.
Like this.
So this is the birth of what we call VDI for 3D visualization.
My neighbour Magnus, who used to work here, told me about the problems.
We have things we can solve with this.
We sat down in a working group.
I forgot to mention Andreas Botten, but it was Magnus, Kristina and Gart.
And then we got Espen from Kulturystyret, Sko Luka from GEO, and Libert.
And then we started working on this project, and eventually got money through the Nordic funds, with a project called Dire, so that we could use it.
And without the fantastic support from USIT, we would never have been able to do this.
Now I'm going to try to tell you a little bit about what we were able to do in collaboration with USIT.
I'm sure this would never have been possible without a centralized form of USIT.
If you could work with local IT, you wouldn't have had enough competence.
When I talk to my colleagues in Europe, none of them have such an organization as USIT.
So it's impossible to get started without really special competence.
VDI is similar to what we have heard before.
It means Virtual Desktop Interface.
It means that you can have access to either VMware Client or via HTML, and you can log on to persistent or non-persistent machines.
The advantage is that you can sit anywhere in the world, and you can get access to the data machine with a lot of power.
We have a lot of production space, we have a lot of capacity for CPU and GPU, and we have put all of the specialized software on this machine.
A lot of the work was to get the licenses to work on this machine.
It was a lot of work, and we got a lot of help to get it to work.
Everything we want from the software, we have managed to get over to this system.
The big advantage of the VDI system is that we have managed to build together with USYT, so it is a fully interactive service.
It is scalable, so if we get more users or more, we can increase the number of machines, increase CPU, increase GPU and storage.
It can be connected to HPC.
We haven't done that yet, but it's something we want to work with.
We can store data, and most importantly, access to licensed software.
We paid a very expensive license.
Maybe we only use it 20% of the time.
Now we can use the license 100%, and we can share it with all researchers in Europe.
Research groups that don't have the means to come to us and do the analysis, and only need the software for two weeks, will get access to it and will never have access to such software before.
So that's a very, very big advantage.
The way we have set it up structurally is that we have different types of machines for different types of use.
So we have set up some machines that are for users who use it a lot, and who have their own machines that use it.
Then we have some machines that go directly to our laboratory.
It was very useful to have during Covid, when we were not allowed to be all together in the lab, and then people could also sit at home and do
other types of things in VDI than just micro and nanosetting, so it has been used a lot for other things.
And then we have a lot of other machines that are used by more refugee people who have come to work for a very short period of time and then move on.
You can see here that I have put up something called Excite Network.
I haven't explained what it is, but Excite Network is a large e-project
This is a picture of me, Garda, Magnus, Lukas and Libert that we got through three years ago.
XITE is a large research network that gathers everything in Europe and gives free access to these advanced instruments that we work with.
In the first round, we got 65 million from the EU.
In April, we got 140 million kroner.
This will give free access to the best in kidney tomography.
What was interesting about the EU network was that they weren't so interested in our machines, because there are much better machines in Europe.
What they were most interested in was VDI solutions.
In the first round, we got some money for VDI, because I didn't think this was possible to achieve.
But now I see that we have achieved everything we said in the first project, so now we have a much bigger slump to use, so that everyone in this network will use VDI solutions for data treatment later.
So then VDI plays a key role.
It shows that Bira is suddenly an attractive partner in EU projects, because we manage to get a unique collaboration with the EU.
If we hadn't gotten it, we wouldn't have been so attractive out there.
It would never have worked if I had only worked with a local IT.
I also want the EU network to continue
such VDI solutions to other universities in the network, because no one else is able to build it without support from here.
Here I just showed you some of the groups we have.
We have everything from research and industry, and you get to have it all around the world, because it doesn't matter where you sit, and it doesn't matter what kind of background you have.
So we have a lot of different backgrounds, and that makes us very flexible, and of course creates a lot of joint publications and even more collaboration.
The feedback from those who have tested out the systems.
We started with a type of system, and this is to show those of you who are interested in data power.
We had a system with
3 GHz CPU with 4 cores and 24 RAM.
That was too fast.
We upgraded it to a little more RAM and replaced the GPU system.
This system also showed lagging when we had heavy data files.
We made a last update in February this year.
We have gone up to a significant GPU, and now this works very well.
It just shows the scalable possibilities that you can come back and change.
We get extremely good feedback from users on this system.
The advantage we have with VDI at the EU is that we are much more visible out there.
We suddenly become attractive as EU partners.
competitive in education, because it is difficult to try to have the last and best machine all the time, because it costs so much money to always be in the research front on all of the micro-SETs and nano-SETs.
But with this type of technology we become completely unique, and then we become a very attractive co-working partner.
And we see that we get much more efficient collaboration with other universities and save a lot of money on sharing infrastructure and sharing expertise.
Another thing that the EU likes very much, just with VDI, is to look at sustainability goals.
We have a requirement now that we will work more sustainable, and VDI is a very sustainable, healthy
Because it's not just about reducing the number of trips and how long the guests have to stay with us, but we can also provide access remotely, and we can also reduce the number of hardware uses.
Because now everyone doesn't need to have their own heavy PC standing next to a computer that has only used 10% of the time.
Now we have a system that is ongoing and continuously in use.
It is also much more efficient in terms of the use of electricity and the exchange of components.
This was something that the EU also liked very much, just as we wrote it in the last search note.
What challenges do we still have?
It requires a very stable staff to teach people and give them access.
I'm very lucky to have Libert, who takes all the work.
This is an automatic process of giving people access.
Now people need to get a guest account from UiO.
There is also a lot of learning in the system and how to use it.
Persistent machines do not always log out, so you do not have to follow up with the time.
You need a person physically to take care of it, so it takes time and capacity to do it.
But we are very pleased with the system and extremely pleased with the collaboration with USIT and what we have achieved.
We are looking forward to getting full power, because we have really built up the system here.
We can use it to its fullest potential, and it will become a very important tool in our research in the future.
I would like to thank everyone who has been a part of the project, especially Vegard and Mona-Leena, who are very active in my mind, despite being with us and still helping.
We have seen a lot of tweaks and things that have to be arranged all the time, so we are still dependent on having good contacts and good relationships with USIT, and having the people here who are competent and can help us with things that hack or do not work.
If you have any questions, I have put in an address to me and Libert.
If you have any questions right now, you can send us questions later.
We can help you with how to set up VDI.
I'm sure this can be used for many other things at UiO than just the microphone.
Thank you.
Vegard and Mona-Lene, are you here?
In relation to the break, Vegard is also the man to talk to if he is interested in more technical details, because we have been very close to this setup.
As you say, there is a lot of international attention, and this has gone in parallel with the construction of EduCloud, and when we are going to scale this up and look at other use cases, we will drive this up.
It's part of our experience, and the fact that we shouldn't have servers that are idle is very important for us now and in the future, because this is a scarce resource nowadays.
What happened first, the hand-hand damage, or did you start researching things like that?
My students say that I only did this to update my PowerPoint, because I had an injury in my foot eight years ago at Snow Racer.
It showed exactly the same, so I have 25 screws in my ankle.
Ten years later, I got 27 in my other ankle.
I saw that research came first.
So it was just a fluke?
It was just to update my PowerPoint about Titan.
You talked about people coming to the races to scan things.
Yes.
Both natural history and dentistry and dentistry.
Yes.
And that was, for example... There are a lot of tests, right?
Because then you have less time.
So then you want to scan as many tests as possible in the shortest possible time.
Because...
I can't stay in Oslo for long, so I have 200 tests to scan.
It can be a titanium screw, a pole, a fish, or anything.
A fish?
I want to scan as many tests as possible.
I don't have time to analyze the data.
They get it in these VDIs, and they can load it into the data.
Does it look like your already cool animations?
Does it actually look like that?
That was real.
That was real, yes.
Or they send you the samples to us.
When you start looking at the data, you don't always know what to do and what to analyze.
You have to create a wild, and after a while you find out more and more what to do, what to analyze, what to use, what to draw from.
And then I can sit in Granada, or in Brazil, or in Umeå, and then I can sit and do the analysis.
And dig into this material that you can sit and actually look at, very visually.
Cool, cool.
Very good.
Were there any more questions for Håvard here now?
There was something up there, yes.
We can start here.
Hi.
No, it's not really a question, but it's more to us.
I understood it as a coincidence that you came because you have a neighbor named Magnus.
And then there's something with us not being able to advertise what we're doing.
It's a group of people among us.
At vi er ganske gode på det vi holder på med, men vi klarer ikke å reklamere for oss eller få det ut, sant?
Ja, men det er klart at nå var jo dette innovasjon, så dette fantes jo ikke før noen smarte ord har snakket sammen om for så vidt.
Men derfor så prøver vi å snakke om det her så ofte som vi kan, når vi er ute, uansett hva vi er enn i verden, så tar vi alt med å forklare det her for å prøve muligheterne også.
So that others can also use it.
But it's always like that in research, right?
That there are a lot of coincidences that play into the fact that you can make a quantum leap forward.
Yes, I actually have two questions.
The first is, what kind of requirements are there for clients who should be able to show this here on the 3D graphics?
What kind of boundaries must you have?
to the client.
And the other thing I heard once was that the implants that you insert into the body are sometimes worn out and have to be replaced.
And when you do that, you take out the whole thing and insert it again.
And then it's limited to how many times you can do it before the leg no longer handles it.
Are there any implants that you can just unscrew the wear part and screw it on the fixed part?
Because there is no point in replacing the whole thing if only the worn part is damaged.
If this is your implant, you have access to the oral cavity, where there are many bacteria.
After 10 years, there will be a lot of bacteria attached to the implant.
if you are not careful enough with the maintenance.
One in ten, or two in ten, implants fail after ten years.
That's why you can't clean it well enough.
You start to get bacteria that attach to the surface and start to eat on the leg.
Then you start to eat down.
In the end, it is so much that the whole implant becomes loose.
Then you do not get direct contact with the implant.
And then afterwards, it is not a part that wears out, but it is the bacteria that eats up the legs around, if you are not careful enough with hygiene.
But these are things we are doing research on, so we use a lot of this technology.
How can we stop?
How can we clean well enough?
What should we clean with?
Should we use chemical?
Should we use mechanical?
This is a very current problem.
Implantations do not last forever.
I am very satisfied with this.
Bacteria may attach to this, but there is less chance of it being closed in here than in the mouth, because it is easier there.
With the width of the bond, I think Vegard is better at answering the question of what is required.
But it requires a good internet connection.
Can you answer that, Vegard?
I might have to answer that.
the microphone, so people can stream it with it.
4 Mbit, I think I'm going to put in a lot of bits, but it's a bit of an adjustment.
We can also tweak how many frames the user should have and pack sizes and a lot of things like that, so it's quite adaptable in that way.
which is also interesting, but which is very powerful.
Even though Cambridge University should have a lot of money, they do not have access to either HPC or a computer with a little bit of data power.
So they are doing everything from Python and AI on their small laptops.
So they also use the system here to run some AI algorithms.
What is important is that we will try to distinguish between different things, such as legs and implants, when scanning.
It is very easy to do when you have different range contrasts.
If you look at a stone, it would have different range contrasts, but it would also have different volumes and sizes.
We use AI to recognize different patterns.
Cambridge has expertise in segmentation.
They don't have enough data power, and they have to pay money to get data power.
So they use the VDI, so they don't use it in AI models.
They have to pay for data power?
Yes.
Or they sit with their Mac and try to keep up with AI.
It's paradoxical.
We are very lucky to have access to this.
The potential that we have to try to sell out there, with Fox and EduCloud, is something that can be used in EU and NFS searches.
It's unique.
I think we'll take the time we lost afterwards.
I'm curious if you have had any feedback regarding the delay?
If someone is working with VDI and is very far away from Norway, how is the delay in work?
There has been some lagging on the big data programs, especially when we haven't updated them.
Otherwise, the only feedback was that the programs had taken a long time to process.
But after the last update, we haven't had any problems with it after the update, right?
We haven't received any feedback that the programs have been hanging for a very long time after the last update?
No.
I'm thinking more like, you move the mouse and take it as a second.
No, no, that's not a problem at all.
So it's more that the big data programs use a long time on processing.
And then it freezes, then you can't use the mouse because
You use so much of the GPU and CPU.
I feel like I'm done with the screws, and the teeth, and the titanium thing.
Don't step on the roof, and don't ride a snowmobile with the kids.
That was the foot.
But there will be better and better implants, at least in the future, based on the research that is being done.
We take a break now, and it will be up to a quarter to eleven.
So let's come and applause for Howard.