Interview: Jin Woo Jung

 

Jin Woo Jung is a computer science graduate student who is doing research at the Minnesota Dental Research Center for Biomaterials and Biomechanics (MDRCBB), led by Professor Alex Fok (Restorative Sciences), in the School of Dentistry. He has been using MSI for about a year. Mr. Jung was a finalist in the poster competition at the 2013 MSI Research Exhibition with his poster, “Photo-realistic Rendering of Teeth and Restorative Bio-materials Using Monte-Carlo Photon Tracing.” He is in the research group of Associate Professor Gary Meyer (Computer Science and Engineering) and also works with Professor Ralph DeLong (MDRCBB), and Associate Professor Maria Pintado (MDRCBB). Mr. Jung sat down with MSI recently to discuss his research; Professors DeLong and Pintado also participated in the interview.

MSI: What kinds of research do you use MSI for?

Jin Woo Jung: I’m doing light transport simulations to reproduce the photo-realistic appearance of dental tissues and biomaterials on the computer screen. The light path within the volume can be modeled as random walks of photons, and Monte Carlo simulation is able to compute the outgoing radiance from the random walks. And then we synthesize the images that show the realistic translucent objects, using the information we calculate.

MSI: In your poster, you’re modeling materials that will be used in tooth restorations. Tell me what you did to get to this poster.

JJ: Obviously, restorative materials have to have very similar appearance to the tooth. As any dentist will tell you, that is a very difficult problem because the color of the restoration changes when it becomes part of the tooth. Furthermore, it is not easy for dentists to choose the correct shades of restorations for their patients. Well, I’m sure Professor DeLong and Professor Pintado will correct me if I’m wrong about the properties of teeth. A tooth is a heterogeneous object; it consists of three major components that are very different. From the outside working inwards, they are: enamel, dentin, and pulp. Overall a tooth is translucent. We all agree that it looks kind of yellow. That’s not because of the color of the enamel; it’s because of the color of the underlying dentin, which is yellow. The yellow passes through the enamel, which may add some white to the final appearance.

But if we can predict the appearance of the restorations in various situations through a simulation, we can assist the materials engineer to develop restorations with the correct appearances, and dentists to choose the right shades for the restorations. So, that’s why we started this research. First of all, we scanned real teeth using the micro-CT scanner at the MDRCBB, and extracted their geometric information; not only the surface geometry but also the density information inside the volume.

Maria Pintado: This geometric information is also used in my study and teaching on the anatomy of teeth. We have produced a self-learning software package called Tooth Explorer using the images created by Jin Woo.

JJ: Using Avizo and Hypermesh that MSI provides, we segmented the micro-CT data and reconstructed the surface information. We also obtained the optical characteristics of teeth and restorative materials from published papers. Applying all of this information to my simulations, I can render the appearance of the teeth on the computer screen. The picture at the end of the poster shows a rendition of the real teeth, including their surfaces and volumes. The simulated light has all the characteristics that come from real enamel and dentin.

I also simulated restorative materials. The restorative material I used was from 3M ESPE, a division of 3M that manufactures dental products and has a long-term collaboration with MDRCBB. They have the spectrophotometers to measure the optical characteristics of the material, such as scattering, absorption, and anisotropy. I modeled the restorative material to show how shade, color and translucency combined to give off overall appearance.

MSI: Now, you’re a computer science student, and you’re working with the Dental School. Can you talk a little bit about the interdisciplinary aspects of this work?

JJ: We are trying to solve a problem in the field of dentistry using computer graphics. The computer science aspects of this require the appropriate mathematics and optimal computing algorithms using the computational power of modern computers, which leads to a good approximation of the real world. We need to have data for the light scattering and the geometry of the teeth. The field of dentistry and related industries provide the data we can make use of. The simulations have some very practical ends in view ­ that is, assisting the dentists in the real world in shade and color matching. The medical/dental industry is a good practical field that the computer science experts can apply their approaches. That’s how the two fields are working together.

Ralph DeLong: The way this research came about was that we have a problem. The problem is making realistic teeth out of, essentially, numbers. Jin Woo’s advisor in Computer Science [Associate Professor Gary Meyer] is interested in light transfer through materials, so the two requirements fit very well together. The third component of this is 3M. 3M manufactures restorative materials, and there’s always been a problem in dentistry of matching colors to the natural teeth, because if they don’t match, people aren’t happy. For years, dentistry has been trying to find a better way to do this. Right now, it’s still done by eye. You look at a tooth, compare it to a color guide and decide this color is close, so I’ll use it. Generally, you can get a good result. Now, you have things like CAD/CAM [computer-aided design/computer-aided manufacturing] coming into dentistry, where you’re milling restorations, and most of them don’t look very aesthetic. So, if you want to make an aesthetic restoration, you have to mill different materials and put them together. Also, for composite fillings, you take one color and you insert it into the tooth ­ it may or may not give you a good match. If you really want aesthetics, you have to start using multiple colors and put them together ­ that’s an art form. What we’d like to do is capture an image of the tooth, then use a computer using known optical properties of the restorative materials and the teeth, and our software tells us what restorative materials to use. This is a three-way junction between computer science, dentistry, and industry. Much of this development was foreseen in our work on an NIDCR [National Institute of Dental and Craniofacial Research] project called the Virtual Dental Patient.

MSI: That’s very exciting. When you say composites, you mean fillings?

RD: Yes, filling materials.

MSI: So, you’re using computer modeling to simulate the way light hits these materials. I’m guessing this is something that could not be done on a standard desktop computer?

JJ: The difficulty with this simulation is that it requires a lot of computational power, as well as a large amount of memory space. Unlike an analytical approach, Monte-Carlo simulation needs to sample large amount of data to compute an outgoing radiance on the surfaces. Parallel computing with multiple computing nodes is very useful in this kind of problem. In addition, we re-use a lot of intermediate results that we compute for the translucent objects. That’s why large amount of main memory is also helpful in this simulation. If we were running this kind of simulation in my laptop, it would take weeks, if not months. Without huge main memory space, the simulation would waste time on swapping data between main memory and secondary storage. Thanks to MSI, we can save a lot of time.

MSI: Did you use the supercomputers on this, or did you use the labs?

JJ: This is a large simulation that requires a lot of computing power. I used the Windows machines [through the labs] on Iron for the Monte Carlo simulation.

MSI: When you run your calculations, do you get a visualization, or do you get numbers that the manufacturer can use to create these false teeth?

JJ: The final results of this simulation are photo-realistic renderings of teeth and biomaterials. Through changing the optical properties of the restorative materials, we can arrive at the appropriate values for desired appearance as required by the materials scientists and dentists.

MSI: How close are we to the point where 3M will be able to use this?

JJ: It will take some time. One thing I have to overcome is the slow speed of the simulation. If we simulated the physically correct appearance of the teeth and the biomaterials fast enough, the material engineers and dentists would be happy to use this. Right now, we are modeling a real-time algorithm, with recent hardware technologies, based on the current mathematical model. We are expecting this research to be more helpful with better responsiveness. Once we have that, it’s going to be very useful, especially for the material designers, as well as dentists who can take advantage of these approaches.

MSI: So then, 3M will be able to make these materials so that a dentist will be able to build teeth based on the individual patient? Very individualized treatment?

RD: Once he’s got an equation, he needs the optical properties of the materials. 3M would measure those optical properties, and they would be plugged into some sort of a device, possibly a portable spectrometer. The device would capture an image of the tooth, and tell you what material to use. It makes it very easy to identify the right material and how to use it. The device would consider the multiple structures within the tooth, possible filling materials, and guide the dentist how to use them.

This optical information could lead manufacturers to changing colors of the restorative materials. Right now, the colors of the restorative materials are a shot in the dark (no pun intended). They provide a range, but they may not be the best colors to match natural teeth.

One other thing I should mention, Jin Woo gets most of his data from the MDRCBB micro­CT scans, which come out as shades of gray; it’s literally just a bunch of numbers. When he gets through, and you look at the image, it looks just like a natural tooth. There have been NIH SBIR [Small Business Innovation Research] grants given to do something like this, to render a tooth in a dental atlas. The way they had to do it was to take pictures of teeth as they slowly rotated them through different viewing angles, then they combined the pictures to get an apparent 3D image that could be rotated in space; a very tedious process. When you put those pictures up against Jin Woo’s, there’s no difference. And yet his technique is all mathematics with some physics.

Posted on November 13, 2013.

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