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KAIST builds a high-resolution 3D holographic sensor using a single mask
Holographic cameras can provide more realistic images than ordinary cameras thanks to their ability to acquire 3D information about objects. However, existing holographic cameras use interferometers that measure the wavelength and refraction of light through the interference of light waves, which makes them complex and sensitive to their surrounding environment. On August 23, a KAIST research team led by Professor YongKeun Park from the Department of Physics announced a new leap forward in 3D holographic imaging sensor technology. The team proposed an innovative holographic camera technology that does not use complex interferometry. Instead, it uses a mask to precisely measure the phase information of light and reconstruct the 3D information of an object with higher accuracy. < Figure 1. Structure and principle of the proposed holographic camera. The amplitude and phase information of light scattered from a holographic camera can be measured. > The team used a mask that fulfills certain mathematical conditions and incorporated it into an ordinary camera, and the light scattered from a laser is measured through the mask and analyzed using a computer. This does not require a complex interferometer and allows the phase information of light to be collected through a simplified optical system. With this technique, the mask that is placed between the two lenses and behind an object plays an important role. The mask selectively filters specific parts of light,, and the intensity of the light passing through the lens can be measured using an ordinary commercial camera. This technique combines the image data received from the camera with the unique pattern received from the mask and reconstructs an object’s precise 3D information using an algorithm. This method allows a high-resolution 3D image of an object to be captured in any position. In practical situations, one can construct a laser-based holographic 3D image sensor by adding a mask with a simple design to a general image sensor. This makes the design and construction of the optical system much easier. In particular, this novel technology can capture high-resolution holographic images of objects moving at high speeds, which widens its potential field of application. < Figure 2. A moving doll captured by a conventional camera and the proposed holographic camera. When taking a picture without focusing on the object, only a blurred image of the doll can be obtained from a general camera, but the proposed holographic camera can restore the blurred image of the doll into a clear image. > The results of this study, conducted by Dr. Jeonghun Oh from the KAIST Department of Physics as the first author, were published in Nature Communications on August 12 under the title, "Non-interferometric stand-alone single-shot holographic camera using reciprocal diffractive imaging". Dr. Oh said, “The holographic camera module we are suggesting can be built by adding a filter to an ordinary camera, which would allow even non-experts to handle it easily in everyday life if it were to be commercialized.” He added, “In particular, it is a promising candidate with the potential to replace existing remote sensing technologies.” This research was supported by the National Research Foundation’s Leader Research Project, the Korean Ministry of Science and ICT’s Core Hologram Technology Support Project, and the Nano and Material Technology Development Project.
KAIST researchers find the key to overcome the limits in X-ray microscopy
X-ray microscopes have the advantage of penetrating most substances, so internal organs and skeletons can be observed non-invasively through chest X-rays or CT scans. Recently, studies to increase the resolution of X-ray imaging technology are being actively conducted in order to precisely observe the internal structure of semiconductors and batteries at the nanoscale. KAIST (President Kwang Hyung Lee) announced on April 12th that a joint research team led by Professor YongKeun Park of the Department of Physics and Dr. Jun Lim of the Pohang Accelerator Laboratory has succeeded in developing a core technology that can overcome the resolution limitations of existing X-ray microscopes. d This study, in which Dr. KyeoReh Lee participated as the first author, was published on 6th of April in “Light: Science and Application”, a world-renowned academic journal in optics and photonics. (Paper title: Direct high-resolution X-ray imaging exploiting pseudorandomness). X-ray nanomicroscopes do not have refractive lenses. In an X-ray microscope, a circular grating called a concentric zone plate is used instead of a lens. The resolution of an image obtained using the zone plate is determined by the quality of the nanostructure that comprises the plate. There are several difficulties in fabricating and maintaining these nanostructures, which set the limit to the level of resolution for X-ray microscopy. The research team developed a new X-ray nanomicroscopy technology to overcome this problem. The X-ray lens proposed by the research team is in the form of numerous holes punched in a thin tungsten film, and generates random diffraction patterns by diffracting incident X-rays. The research team mathematically identified that, paradoxically, the high-resolution information of the sample was fully contained in these random diffraction patterns, and actually succeeded in extracting the information and imaging the internal states of the samples. The imaging method using the mathematical properties of random diffraction was proposed and implemented in the visible light band for the first time by Dr. KyeoReh Lee and Professor YongKeun Park in 2016*. This study uses the results of previous studies to solve the difficult, lingering problem in the field of the X-ray imaging. ※ "Exploiting the speckle-correlation scattering matrix for a compact reference-free holographic image sensor." Nature communications 7.1 (2016): 13359. The resolution of the image of the constructed sample has no direct correlation with the size of the pattern etched on the random lens used. Based on this idea, the research team succeeded in acquiring images with 14 nm resolution (approximately 1/7 the size of the coronavirus) by using random lenses made in a circular pattern with a diameter of 300 nm. The imaging technology developed by this research team is a key fundamental technology that can enhance the resolution of X-ray nanomicroscopy, which has been blocked by limitations of the production of existing zone plates. The first author and one of the co-corresponding author, Dr. KyeoReh Lee of KAIST Department of Physics, said, “In this study, the resolution was limited to 14 nm, but if the next-generation X-ray light source and high-performance X-ray detector are used, the resolution would exceed that of the conventional X-ray nano-imaging and approach the resolution of an electron microscope.” and added, “Unlike an electron microscope, X-rays can observe the internal structure without damaging the sample, so it will be able to present a new standard for non-invasive nanostructure observation processes such as quality inspections for semiconductors.”. The co-corresponding author, Dr. Jun Lim of the Pohang Accelerator Laboratory, said, “In the same context, the developed image technology is expected to greatly increase the performance in the 4th generation multipurpose radiation accelerator which is set to be established in Ochang of the Northern Chungcheong Province.” This research was conducted with the support through the Research Leader Program and the Sejong Science Fellowship of the National Research Foundation of Korea. Fig. 1. Designed diffuser as X-ray imaging lens. a, Schematic of full-field transmission X-ray microscopy. The attenuation (amplitude) map of a sample is measured. The image resolution (dx) is limited by the outermost zone width of the zone plate (D). b, Schematic of the proposed method. A designed diffuser is used instead of a zone plate. The image resolution is finer than the hole size of the diffuser (dx << D). Fig. 2. The left panel is a surface electron microscopy (SEM) image of the X-ray diffuser used in the experiment. The middle panel shows the design of the X-ray diffuser, and there is an inset in the middle of the panel that shows a corresponding part of the SEM image. The right panel shows an experimental random X-ray diffraction pattern, also known as a speckle pattern, obtained from the X-ray diffuser. Fig. 3. Images taken from the proposed randomness-based X-ray imaging (bottom) and the corresponding surface electron microscope (SEM) images (top).
Tomographic Measurement of Dielectric Tensors
Dielectric tensor tomography allows the direct measurement of the 3D dielectric tensors of optically anisotropic structures A research team reported the direct measurement of dielectric tensors of anisotropic structures including the spatial variations of principal refractive indices and directors. The group also demonstrated quantitative tomographic measurements of various nematic liquid-crystal structures and their fast 3D nonequilibrium dynamics using a 3D label-free tomographic method. The method was described in Nature Materials. Light-matter interactions are described by the dielectric tensor. Despite their importance in basic science and applications, it has not been possible to measure 3D dielectric tensors directly. The main challenge was due to the vectorial nature of light scattering from a 3D anisotropic structure. Previous approaches only addressed 3D anisotropic information indirectly and were limited to two-dimensional, qualitative, strict sample conditions or assumptions. The research team developed a method enabling the tomographic reconstruction of 3D dielectric tensors without any preparation or assumptions. A sample is illuminated with a laser beam with various angles and circularly polarization states. Then, the light fields scattered from a sample are holographically measured and converted into vectorial diffraction components. Finally, by inversely solving a vectorial wave equation, the 3D dielectric tensor is reconstructed. Professor YongKeun Park said, “There were a greater number of unknowns in direct measuring than with the conventional approach. We applied our approach to measure additional holographic images by slightly tilting the incident angle.” He said that the slightly tilted illumination provides an additional orthogonal polarization, which makes the underdetermined problem become the determined problem. “Although scattered fields are dependent on the illumination angle, the Fourier differentiation theorem enables the extraction of the same dielectric tensor for the slightly tilted illumination,” Professor Park added. His team’s method was validated by reconstructing well-known liquid crystal (LC) structures, including the twisted nematic, hybrid aligned nematic, radial, and bipolar configurations. Furthermore, the research team demonstrated the experimental measurements of the non-equilibrium dynamics of annihilating, nucleating, and merging LC droplets, and the LC polymer network with repeating 3D topological defects. “This is the first experimental measurement of non-equilibrium dynamics and 3D topological defects in LC structures in a label-free manner. Our method enables the exploration of inaccessible nematic structures and interactions in non-equilibrium dynamics,” first author Dr. Seungwoo Shin explained. -PublicationSeungwoo Shin, Jonghee Eun, Sang Seok Lee, Changjae Lee, Herve Hugonnet, Dong Ki Yoon, Shin-Hyun Kim, Jongwoo Jeong, YongKeun Park, “Tomographic Measurement ofDielectric Tensors at Optical Frequency,” Nature Materials March 02, 2022 (https://doi.org/10/1038/s41563-022-01202-8) -ProfileProfessor YongKeun ParkBiomedical Optics Laboratory (http://bmol.kaist.ac.kr)Department of PhysicsCollege of Natural SciencesKAIST
Label-Free Multiplexed Microtomography of Endogenous Subcellular Dynamics Using Deep Learning
AI-based holographic microscopy allows molecular imaging without introducing exogenous labeling agents A research team upgraded the 3D microtomography observing dynamics of label-free live cells in multiplexed fluorescence imaging. The AI-powered 3D holotomographic microscopy extracts various molecular information from live unlabeled biological cells in real time without exogenous labeling or staining agents. Professor YongKeum Park’s team and the startup Tomocube encoded 3D refractive index tomograms using the refractive index as a means of measurement. Then they decoded the information with a deep learning-based model that infers multiple 3D fluorescence tomograms from the refractive index measurements of the corresponding subcellular targets, thereby achieving multiplexed micro tomography. This study was reported in Nature Cell Biology online on December 7, 2021. Fluorescence microscopy is the most widely used optical microscopy technique due to its high biochemical specificity. However, it needs to genetically manipulate or to stain cells with fluorescent labels in order to express fluorescent proteins. These labeling processes inevitably affect the intrinsic physiology of cells. It also has challenges in long-term measuring due to photobleaching and phototoxicity. The overlapped spectra of multiplexed fluorescence signals also hinder the viewing of various structures at the same time. More critically, it took several hours to observe the cells after preparing them. 3D holographic microscopy, also known as holotomography, is providing new ways to quantitatively image live cells without pretreatments such as staining. Holotomography can accurately and quickly measure the morphological and structural information of cells, but only provides limited biochemical and molecular information. The 'AI microscope' created in this process takes advantage of the features of both holographic microscopy and fluorescence microscopy. That is, a specific image from a fluorescence microscope can be obtained without a fluorescent label. Therefore, the microscope can observe many types of cellular structures in their natural state in 3D and at the same time as fast as one millisecond, and long-term measurements over several days are also possible. The Tomocube-KAIST team showed that fluorescence images can be directly and precisely predicted from holotomographic images in various cells and conditions. Using the quantitative relationship between the spatial distribution of the refractive index found by AI and the major structures in cells, it was possible to decipher the spatial distribution of the refractive index. And surprisingly, it confirmed that this relationship is constant regardless of cell type. Professor Park said, “We were able to develop a new concept microscope that combines the advantages of several microscopes with the multidisciplinary research of AI, optics, and biology. It will be immediately applicable for new types of cells not included in the existing data and is expected to be widely applicable for various biological and medical research.” When comparing the molecular image information extracted by AI with the molecular image information physically obtained by fluorescence staining in 3D space, it showed a 97% or more conformity, which is a level that is difficult to distinguish with the naked eye. “Compared to the sub-60% accuracy of the fluorescence information extracted from the model developed by the Google AI team, it showed significantly higher performance,” Professor Park added. This work was supported by the KAIST Up program, the BK21+ program, Tomocube, the National Research Foundation of Korea, and the Ministry of Science and ICT, and the Ministry of Health & Welfare. -Publication Hyun-seok Min, Won-Do Heo, YongKeun Park, et al. “Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning,” Nature Cell Biology (doi.org/10.1038/s41556-021-00802-x) published online December 07 2021. -Profile Professor YongKeun Park Biomedical Optics Laboratory Department of Physics KAIST
Deep-Learning and 3D Holographic Microscopy Beats Scientists at Analyzing Cancer Immunotherapy
Live tracking and analyzing of the dynamics of chimeric antigen receptor (CAR) T-cells targeting cancer cells can open new avenues for the development of cancer immunotherapy. However, imaging via conventional microscopy approaches can result in cellular damage, and assessments of cell-to-cell interactions are extremely difficult and labor-intensive. When researchers applied deep learning and 3D holographic microscopy to the task, however, they not only avoided these difficultues but found that AI was better at it than humans were. Artificial intelligence (AI) is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place. The AI transformed work that, if performed manually by scientists, would otherwise be incredibly labor-intensive and time-consuming into one that is not only effortless but done better than they could have done it themselves. The research, conducted by the team of Professor YongKeun Park from the Department of Physics, appeared in the journal eLife last December. A critical stage in the development of the human immune system’s ability to respond not just generally to any invader (such as pathogens or cancer cells) but specifically to that particular type of invader and remember it should it attempt to invade again is the formation of a junction between an immune cell called a T-cell and a cell that presents the antigen, or part of the invader that is causing the problem, to it. This process is like when a picture of a suspect is sent to a police car so that the officers can recognize the criminal they are trying to track down. The junction between the two cells, called the immunological synapse, or IS, is the key process in teaching the immune system how to recognize a specific type of invader. Since the formation of the IS junction is such a critical step for the initiation of an antigen-specific immune response, various techniques allowing researchers to observe the process as it happens have been used to study its dynamics. Most of these live imaging techniques rely on fluorescence microscopy, where genetic tweaking causes part of a protein from a cell to fluoresce, in turn allowing the subject to be tracked via fluorescence rather than via the reflected light used in many conventional microscopy techniques. However, fluorescence-based imaging can suffer from effects such as photo-bleaching and photo-toxicity, preventing the assessment of dynamic changes in the IS junction process over the long term. Fluorescence-based imaging still involves illumination, whereupon the fluorophores (chemical compounds that cause the fluorescence) emit light of a different color. Photo-bleaching or photo-toxicity occur when the subject is exposed to too much illumination, resulting in chemical alteration or cellular damage. One recent option that does away with fluorescent labelling and thereby avoids such problems is 3D holographic microscopy or holotomography (HT). In this technique, the refractive index (the way that light changes direction when encountering a substance with a different density—why a straw looks like it bends in a glass of water) is recorded in 3D as a hologram. Until now, HT has been used to study single cells, but never cell-cell interactions involved in immune responses. One of the main reasons is the difficulty of “segmentation,” or distinguishing the different parts of a cell and thus distinguishing between the interacting cells; in other words, deciphering which part belongs to which cell. Manual segmentation, or marking out the different parts manually, is one option, but it is difficult and time-consuming, especially in three dimensions. To overcome this problem, automatic segmentation has been developed in which simple computer algorithms perform the identification. “But these basic algorithms often make mistakes,” explained Professor YongKeun Park, “particularly with respect to adjoining segmentation, which of course is exactly what is occurring here in the immune response we’re most interested in.” So, the researchers applied a deep learning framework to the HT segmentation problem. Deep learning is a type of machine learning in which artificial neural networks based on the human brain recognize patterns in a way that is similar to how humans do this. Regular machine learning requires data as an input that has already been labelled. The AI “learns” by understanding the labeled data and then recognizes the concept that has been labelled when it is fed novel data. For example, AI trained on a thousand images of cats labelled “cat” should be able to recognize a cat the next time it encounters an image with a cat in it. Deep learning involves multiple layers of artificial neural networks attacking much larger, but unlabeled datasets, in which the AI develops its own ‘labels’ for concepts it encounters. In essence, the deep learning framework that KAIST researchers developed, called DeepIS, came up with its own concepts by which it distinguishes the different parts of the IS junction process. To validate this method, the research team applied it to the dynamics of a particular IS junction formed between chimeric antigen receptor (CAR) T-cells and target cancer cells. They then compared the results to what they would normally have done: the laborious process of performing the segmentation manually. They found not only that DeepIS was able to define areas within the IS with high accuracy, but that the technique was even able to capture information about the total distribution of proteins within the IS that may not have been easily measured using conventional techniques. “In addition to allowing us to avoid the drudgery of manual segmentation and the problems of photo-bleaching and photo-toxicity, we found that the AI actually did a better job,” Professor Park added. The next step will be to combine the technique with methods of measuring how much physical force is applied by different parts of the IS junction, such as holographic optical tweezers or traction force microscopy. -Profile Professor YongKeun Park Department of Physics Biomedical Optics Laboratory http://bmol.kaist.ac.kr KAIST
Professor YongKeun Park Wins the 2018 Fumio Okano Award
(Professor Park) Professor YongKeun Park from the Department of Physics won the 2018 Fumio Okano Award in recognition of his contributions to 3D display technology development during the annual conference of the International Society for Optics and Photonics (SPIE) held last month in Orlando, Florida in the US. The Fumio Okano Best 3D Paper Prize is presented annually in memory of Dr. Fumio Okano, a pioneer and innovator of 3D displays who passed away in 2013, for his contributions to the field of 3D TVs and displays. The award is sponsored by NHK-ES. Professor Park and his team are developing novel technology for measuring and visualizing 3D images by applying random light scattering. He has published numerous papers on 3D holographic camera technology and 3000x enhanced performance of 3D holographic displays in renowned international journals such as Nature Photonics, Nature Communications, and Science Advances. His technology has drawn international attention from renowned media outlets including Newsweek and Forbes. He has established two startups to commercialize his technology. Tomocube specializes in 3D imaging microscopes using holotomographic technology and the company exports their products to several countries including the US and Japan. The.Wave.Talk is exploring technology for examining pre-existing bacteria anywhere and anytime. Professor Park’s innovations have already been recognized in and out of KAIST. In February, he was selected as the KAISTian of the Year for his outstanding research, commercialization, and startups. He was also decorated with the National Science Award in April by the Ministry of Science and ICT and the Hong Jin-Ki Innovation Award later in May by the Yumin Cultural Foundation. Professor Park said, “3D holography is emerging as a significant technology with growing potential and positive impacts on our daily lives. However, the current technology lags far behind the levels displayed in SF movies. We will do our utmost to reach this level with more commercialization."
Meet the KAISTian of 2017, Professor YongKeun Park
Professor YongKeun Park from the Department of Physics is one of the star professors in KAIST. Rising to the academic stardom, Professor Park’s daily schedule is filled with series of business meetings in addition to lab meetings and lectures. The year 2017 must have been special for him. During the year, he published numerous papers in international journals, such as Nature Photonics, Nature Communications and Science Advances. These high performances drew international attention from renowned media, including Newsweek and Forbes. Moreover, recognizing his research performance, he was elected as a fellow member of the Optical Society (OSA) in his mid-30s. Noting that the members’ age ranges from late 50s to early 60s, Professor Park’s case considered to be quite exceptional. Adding to his academic achievement, he has launched two startups powered of his own technologies. One is called Tomocube, a company specialized in 3-D imaging microscope using holotomography technology. His company is currently exporting the products to multiple countries, including the United States and Japan. The other one is The.Wave.Talk which has technologies for examining pre-existing bacteria anywhere and anytime. His research career and entrepreneurship are well deserved recipient of many honors. At the 2018 kick-off ceremony, Professor Park was awarded the KAISTian of 2017 in recognition of his developing holographic measure and control technology as well as founding a new field for technology application. KAISTian of the Year, first presented in 2001, is an award to recognize the achievements and exemplary contribution of KAIST member who has put significant effort nationally and internationally, enhancing the value of KAIST. While receiving the award, he thanked his colleagues and his students who have achieved this far together. He said, “I would like to thank KAIST for providing environment for young professors like me so that we can engage themselves in research. Also, I would like to mention that I am an idea seeder and my students do the most of the research. So, I appreciate my students for their hard works, and it is very pleasure to have them. Lastly, I thank the professors for teaching these outstanding students. I feel great responsibility over this title. I will dedicate myself to make further progress in commercializing technology in KAIST.” Expecting his successful startup cases as a model and great inspiration to students as well as professors, KAIST interviewed Professor Park. Q What made you decide to found your startups? A I believed that my research areas could be further used. As a professor, I believe that it is a university’s role to create added value through commercializing technology and creating startups. Q You have co-founded two startups. What is your role in each company? A So, basically I have two full-time jobs, professor in KAIST and CTO in Tomocube. After transferring the technology, I hold the position of advisor in The.Wave.Talk. (Holographic images captured by the product Professor Park developed) Q Do your students also participate in your companies or can they? A No, the school and companies are separate spaces; in other words, they are not participating in my companies. They have trained my employees when transferring the technologies, but they are not directly working for the companies. However, they can participate if they want to. If there’s a need to develop a certain technology, an industry-academia contract can be made. According to the agreement, students can work for the companies. Q Were there any hardships when preparing the startups? A At the initial stage, I did not have a financial problem, thanks to support from Startup KAIST. Yet, inviting capital is the beginning, and I think every step I made to operate, generate revenue, and so on is not easy. Q Do you believe KAIST is startup-friendly? A Yes, there’s no school like KAIST in Korea and any other country. Besides various programs to support startup activities, Startup KAIST has many professors equipped with a great deal of experience. Therefore, I believe that KAIST provides an excellent environment for both students and professors to create startups. Q Do you have any suggestion to KAIST institutionally? A Well, I would like to make a comment to students and professors in KAIST. I strongly recommend them to challenge themselves by launching startups if they have good ideas. Many students wish to begin their jobs in government-funded research institutes or major corporates, but I believe that engaging in a startup company will also give them valuable and very productive experience. Unlike before, startup institutions are well established, so attracting good capital is not so hard. There are various activities offered by Startup KAIST, so it’s worthwhile giving it a try. Q What is your goal for 2018 as a professor and entrepreneur? A I don’t have a grand plan, but I will work harder to produce good students with new topics in KAIST while adding power to my companies to grow bigger. By Se Yi Kim from the PR Office
Professor YongKeun Park Elected as a Fellow of the Optical Society
Professor YongKeun Park, from the Department of Physics at KAIST, was elected as a fellow member of the Optical Society (OSA) in Washington, D.C. on September 12. Fellow membership is given to members who have made a significant contribution to the advancement of optics and photonics. Professor Park was recognized for his research on digital holography and wavefront control technology. Professor Park has been producing outstanding research outcomes in the field of holographic technology and light scattering control since joining KAIST in 2010. In particular, he developed and commercialized technology for a holographic telescope. He applied it to various medical and biological research projects, leading the field worldwide. In the past, cells needed to be dyed with fluorescent materials to capture a 3-D image. However, Professor Park’s holotomography (HT) technology can capture 3-D images of living cells and tissues in real time without color dyeing. This technology allows diversified research in the biological and medical field. Professor Park established a company, Tomocube, Inc. in 2015 to commercialize the technology. In 2016, he received funding from SoftBank Ventures and Hanmi Pharmaceutical. Currently, major institutes, including MIT, the University of Pittsburgh, the German Cancer Research Center, and Seoul National University Hospital are using his equipment. Recently, Professor Park and his team developed technology based on light scattering measurements. With this technology, they established a company called The Wave Talk and received funding from various organizations, such as NAVER. Its first product is about to be released. Professor Park said, “I am glad to become a fellow member based on the research outcomes I produced since I was appointed as a professor at KAIST. I would like to thank the excellent researchers as well as the school for its support. I will devote myself to continuously producing novel outcomes in both basic and applied fields.” Professor Park has published nearly 100 papers in renowned journals including Nature Photonics, Nature Communications, Science Advances, and Physical Review Letters.
Fast, Accurate 3D Imaging to Track Optically-Trapped Particles
KAIST researchers published an article on the development of a novel technique to precisely track the 3-D positions of optically-trapped particles having complicated geometry in high speed in the April 2015 issue of Optica. Optical tweezers have been used as an invaluable tool for exerting micro-scale force on microscopic particles and manipulating three-dimensional (3-D) positions of particles. Optical tweezers employ a tightly-focused laser whose beam diameter is smaller than one micrometer (1/100 of hair thickness), which generates attractive force on neighboring microscopic particles moving toward the beam focus. Controlling the positions of the beam focus enabled researchers to hold the particles and move them freely to other locations so they coined the name “optical tweezers.” To locate the optically-trapped particles by a laser beam, optical microscopes have usually been employed. Optical microscopes measure light signals scattered by the optically-trapped microscopic particles and the positions of the particles in two dimensions. However, it was difficult to quantify the particles’ precise positions along the optic axis, the direction of the beam, from a single image, which is analogous to the difficulty of determining the front and rear positions of objects when closing an eye due to a lack of depth perception. Furthermore, it became more difficult to measure precisely 3-D positions of particles when scattered light signals were distorted by optically-trapped particles having complicated shapes or other particles occlude the target object along the optic axis. Professor YongKeun Park and his research team in the Department of Physics at the Korea Advanced Institute of Science and Technology (KAIST) employed an optical diffraction tomography (ODT) technique to measure 3-D positions of optically-trapped particles in high speed. The principle of ODT is similar to X-ray CT imaging commonly used in hospitals for visualizing the internal organs of patients. Like X-ray CT imaging, which takes several images from various illumination angles, ODT measures 3-D images of optically-trapped particles by illuminating them with a laser beam in various incidence angles. The KAIST team used optical tweezers to trap a glass bead with a diameter of 2 micrometers, and moved the bead toward a white blood cell having complicated internal structures. The team measured the 3-D dynamics of the white blood cell as it responded to an approaching glass bead via ODT in the high acquisition rate of 60 images per second. Since the white blood cell screens the glass bead along an optic axis, a conventionally-used optical microscope could not determine the 3-D positions of the glass bead. In contrast, the present method employing ODT localized the 3-D positions of the bead precisely as well as measured the composition of the internal materials of the bead and the white blood cell simultaneously. Professor Park said, “Our technique has the advantage of measuring the 3-D positions and internal structures of optically-trapped particles in high speed without labelling exogenous fluorescent agents and can be applied in various fields including physics, optics, nanotechnology, and medical science.” Kyoohyun Kim, the lead author of this paper (“Simultaneous 3D Visualization and Position Tracking of Optically Trapped Particles Using Optical Diffraction Tomography”), added, “This ODT technique can also apply to cellular-level surgeries where optical tweezers are used to manipulate intracellular organelles and to display in real time and in 3-D the images of the reaction of the cell membrane and nucleus during the operation or monitoring the recovery process of the cells from the surgery.” The research results were published as the cover article in the April 2014 issue of Optica, the newest journal launched last year by the Optical Society of America (OSA) for rapid dissemination of high-impact results related to optics. Figure 1: This picture shows the concept image of tweezing an optically-trapped glass bead on the cellular membrane of a white blood cell. Figure 2: High-speed 3-D images produced from optical diffraction tomography technique
Ultra-high Resolution 2-dimentional Real-time Image Capture with Super Lens
Ultra-high Resolution 2-dimentional Real-time Image Capture with Super Lens Applications to high-precision semiconductor processing or intracellular structures observation are possible. A joint research team led by Professors Yongkeun Park and Yong-Hoon Cho from the Department of Physics, KAIST, has succeeded in capturing real-time 2D images at a resolution of 100 nm (nanometers), which was impossible with optical lens due to the diffraction limit of light until now. Its future application includes high-precision semiconductor manufacturing process or observation of intracellular structures. This research follows the past research of the super-lens developed by Professor Park last April, using paint spray to observe images that have three times higher resolution than those discovered by conventional optical lens. Since optical lens utilize the refraction of light, the diffraction limit, which prevents achieving focus smaller than the wavelength of light, has always been a barrier for acquiring high-resolution images. In the past, it was impossible to observe objects less than the size of 200 to 300 nm in the visible light spectrum. In order to solve the problem of near-field extinction due to scattering of light, the research team used spray paint consisting of nano-particles massed with dense scattering materials to obtain high-resolution information. Then, by calculating and restoring the first scattering shape of light using the time reversibility of light, the researchers were able to overcome the diffraction limit. The original position of an object to be observed is obtained by deriving the complex trajectory of the light, and reversing the time to locate the particular position of the object. Professor Park said, “This new technology can be used as the core technology in all fields which require optical measurement and control. The existing electron microscopy cannot observe cells without destroying them, but the new technology allows us to visualize at ultra-high resolution without destruction.” The research results were published online in the 9th edition of Physical Review Letters, a prestigious international journal in the field of physics.
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