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3. See-Through Type 3D Head-Mounted Display–Based Surgical Microscope System for Microsurgery: A Feasibility Study

Author

Kim, Cheol-Hwan, Ryu, Seon-Young, Yoon, Ji-Young, Lee, Hyoung-Kwon, Choi, Nak-Gu, Park, Il-Ho, and Choi, Hae-Young

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundThe surgical microscope is used primarily for microsurgeries, which are more complicated than other surgical procedures and require delicate tasks for a long time. Therefore, during these surgical procedures, surgeons experience back and neck pain. To solve this problem, new technology, such as wearable displays, is required to help surgeons maintain comfortable postures and enjoy advanced functionality during microsurgery. ObjectiveThe objective of this study was to develop a surgical microscope system that would work with wearable devices. It would include a head-mounted display (HMD) that can offer 3D surgical images and allow a flexible and comfortable posture instead of fixed eyepieces of surgical microscope and can also provide peripheral visual field with its optical see-through function. MethodsWe designed and fabricated a surgical microscope system that incorporates a see-through type 3D HMD, and we developed an image processing software to provide better image quality. The usability of the proposed system was confirmed with preclinical examination. Seven ENT (ear, nose, and throat) surgical specialists and 8 residents performed a mock surgery—axillary lymph node dissection on a rat. They alternated between looking through the eyepieces of the surgical microscope and viewing a 3D HMD screen connected to the surgical microscope. We examined the success of the surgery and asked the specialists and residents to grade eye fatigue on a scale of 0 (none) to 6 (severe) and posture discomfort on a scale of 1 (none) to 5 (severe). Furthermore, a statistical comparison was performed using 2-tailed paired t test, and P=.00083 was considered significant. ResultsAlthough 3D HMD case showed a slightly better result regarding visual discomfort (P=.097), the average eye fatigue was not significantly different between eyepiece and 3D HMD cases (P=.79). However, the average posture discomfort, especially in neck and shoulder, was lower with 3D HMD display use than with eyepiece use (P=.00083). ConclusionsWe developed a see-through type 3D HMD–based surgical microscope system and showed through preclinical testing that the system could help reduce posture discomfort. The proposed system, with its advanced functions, could be a promising new technique for microsurgery.

Published
2019
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9. Age- and ethnic-driven molecular and clinical disparity of East Asian breast cancers

Author

Lee, Ji Yoon, Lee, Ji Won, Chung, Min Sung, Choi, Jong Gwon, Sim, Sung Hoon, Kim, Hyo Jeong, Kim, Jeong Eun, Lee, Kyoung Eun, Park, Yeon Hee, Kang, Myoung Joo, Ahn, Mi Sun, Chae, Yee Soo, Park, Ji Hyun, Kim, Jee Hyun, Kim, Gun Min, Byun, Jae Ho, Park, Keon Uk, Kim, Ju Won, Jung, Seung Pil, Lee, Jung Hyun, An, Jung Seok, Jang, Byunghyun, Yoon, Dayoung, Kim, Jiwon, Hong, Jisoo, Koo, Harim, Cho, Kyu Ran, Kim, Cheol Yong, Sa, Jason K., and Park, Kyong Hwa

Published
2024
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11. A Machine Learning Approach to Two-Stage Adaptive Robust Optimization

Author

Bertsimas, Dimitris and Kim, Cheol Woo

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract

We propose an approach based on machine learning to solve two-stage linear adaptive robust optimization (ARO) problems with binary here-and-now variables and polyhedral uncertainty sets. We encode the optimal here-and-now decisions, the worst-case scenarios associated with the optimal here-and-now decisions, and the optimal wait-and-see decisions into what we denote as the strategy. We solve multiple similar ARO instances in advance using the column and constraint generation algorithm and extract the optimal strategies to generate a training set. We train a machine learning model that predicts high-quality strategies for the here-and-now decisions, the worst-case scenarios associated with the optimal here-and-now decisions, and the wait-and-see decisions. We also introduce an algorithm to reduce the number of different target classes the machine learning algorithm needs to be trained on. We apply the proposed approach to the facility location, the multi-item inventory control and the unit commitment problems. Our approach solves ARO problems drastically faster than the state-of-the-art algorithms with high accuracy.

Published
2023

12. Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach

Author

Bertsimas, Dimitris and Kim, Cheol Woo

Subjects
Computer Science - Machine Learning
Abstract

We propose a machine learning approach to the optimal control of multiclass fluid queueing networks (MFQNETs) that provides explicit and insightful control policies. We prove that a threshold type optimal policy exists for MFQNET control problems, where the threshold curves are hyperplanes passing through the origin. We use Optimal Classification Trees with hyperplane splits (OCT-H) to learn an optimal control policy for MFQNETs. We use numerical solutions of MFQNET control problems as a training set and apply OCT-H to learn explicit control policies. We report experimental results with up to 33 servers and 99 classes that demonstrate that the learned policies achieve 100\% accuracy on the test set. While the offline training of OCT-H can take days in large networks, the online application takes milliseconds.

Published
2023

16. The Role of the Smallest Molecule Hydrogen Overcoming Ageing-Related Disease

Author

He, Wenjing, Rahman, Md. Habibur, Mo, Chaodeng, Vongdouangchanh, Arounnapha, Kim, Cheol-Su, Lee, Kyu-Jae, Dhalla, Naranjan S., Series Editor, Bolli, Roberto, Editorial Board Member, Goyal, Ramesh, Editorial Board Member, Kartha, Chandrasekharan, Editorial Board Member, Kirshenbaum, Lorrie, Editorial Board Member, Makino, Naoki, Editorial Board Member, Mehta, Jawahar L. L., Editorial Board Member, Ostadal, Bohuslav, Editorial Board Member, Pierce, Grant N., Editorial Board Member, Slezak, Jan, Editorial Board Member, Varro, Andras, Editorial Board Member, Werdan, Karl, Editorial Board Member, Weglicki, William B., Editorial Board Member, and Kura, Branislav, editor

Published
2024
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17. Gate-tunable quantum pathways of high harmonic generation in graphene

Author

Cha, Soonyoung, Kim, Minjeong, Kim, Youngjae, Choi, Shinyoung, Kang, Sejong, Kim, Hoon, Yoon, Sangho, Moon, Gunho, Kim, Taeho, Lee, Ye Won, Cho, Gil Young, Park, Moon Jeong, Kim, Cheol-Joo, Kim, B. J., Lee, JaeDong, Jo, Moon-Ho, and Kim, Jonghwan

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Physics - Optics
Abstract

Under strong laser fields, electrons in solids radiate high-harmonic fields by travelling through quantum pathways in Bloch bands in the sub-laser-cycle timescales. Understanding these pathways in the momentum space through the high-harmonic radiation can enable an all-optical ultrafast probe to observe coherent lightwave-driven processes and measure electronic structures as recently demonstrated for semiconductors. However, such demonstration has been largely limited for semimetals because the absence of the bandgap hinders an experimental characterization of the exact pathways. In this study, by combining electrostatic control of chemical potentials with HHG measurement, we resolve quantum pathways of massless Dirac fermions in graphene under strong laser fields. Electrical modulation of HHG reveals quantum interference between the multi-photon interband excitation channels. As the light-matter interaction deviates beyond the perturbative regime, elliptically polarized laser fields efficiently drive massless Dirac fermions via an intricate coupling between the interband and intraband transitions, which is corroborated by our theoretical calculations. Our findings pave the way for strong-laser-field tomography of Dirac electrons in various quantum semimetals and their ultrafast electronics with a gate control., Comment: 33 pages, 4 figures, Soonyoung Cha and Minjeong Kim contributed equally to this work, To whom correspondence should be addressed: jonghwankim@postech

Published
2022
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20. A Case of The Reduction of Symptoms, But No Change on The CT Scanning in HNP by Oriental Medical Treatment Added Mori cortex-Bee Venom Acupuncture

Author

Lee, Byung-Hoon, Kim, Cheol-Hong, Seo, Jung-Chul, Youn, Hyoun-Min, Song, Choon-Ho, Ahn, Chang-Beohm, and Jang, Kyung-Jeon

Subjects
Mori Cortex-bee venom acupuncture, reduction, HNP, conservative therapy, Medicine, Miscellaneous systems and treatments, RZ409.7-999, Therapeutics. Pharmacology, RM1-950
Abstract

By process of treatment for a case which diagnosed as HNP of left posterolateral aspect of L4/5 disc and treated from the 10th, May 2001 to the 23rd, Jun 2001, the results are as follows. Method & Results : This patient was medicated Hwallaktang-gami, taken acupuncture, phototherapy, TENS, electric acupuncture, exercises, Mori Cortex-bee venom acupuncture. As a result, the patient's clinical symptom were improved but a computed tomagraphy confirmed L4/5 and L5/S1 HNP was not changed as seen on repeated CT scanning. Conclusion : These results suggest that among conservative therapies the oriental medical treatments including Mori Cortex-bee venom acupuncture improve clinical symptom effectively. But in this case, the structure of herniated disc was not changed.

Published
2001
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32. Statistically unbiased prediction enables accurate denoising of voltage imaging data

Author

Eom, Minho, Han, Seungjae, Park, Pojeong, Kim, Gyuri, Cho, Eun-Seo, Sim, Jueun, Lee, Kang-Han, Kim, Seonghoon, Tian, He, Böhm, Urs L., Lowet, Eric, Tseng, Hua-an, Choi, Jieun, Lucia, Stephani Edwina, Ryu, Seung Hyun, Rózsa, Márton, Chang, Sunghoe, Kim, Pilhan, Han, Xue, Piatkevich, Kiryl D., Choi, Myunghwan, Kim, Cheol-Hee, Cohen, Adam E., Chang, Jae-Byum, and Yoon, Young-Gyu

Published
2023
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