Poly-film Greenhouses of Korea

Seungwan Lee,Sang Kun Park,Joong Choon Park 한국원예학회 2008 한국원예학회 기타간행물 Vol.- No.-

High-energy industrial 2D X-ray imaging system with effective nonlocal means denoising for nondestructive testing

Lee, Seungwan,Cho, Heemoon,Lee, Youngjin Elsevier 2019 Nuclear Instruments & Methods in Physics Research. Vol.925 No.-

<P><B>Abstract</B></P> <P>High-energy industrial X-ray imaging systems are widely used in the field of nondestructive testing for the detection of defects in mechanical material. To improve the defect detection ratio, it is highly important to reduce the amount of noise in this process. The purpose of this study is to develop a nonlocal means denoising algorithm in order to evaluate noise characteristics in a 450 kVp high-energy industrial X-ray imaging system. The analysis approach is tested on two phantom images, and image performance is evaluated by visual assessment, as well as the normalized noise power spectrum, contrast to noise ratio, and coefficient of variation. Improvement in image performance is attributed to the use of NLM denoising algorithm on high-energy industrial X-ray images, and results demonstrate that the proposed algorithm effectively reduces image noise.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Experimental study of established high-energy industrial X-ray imaging system. </LI> <LI> Nonlocal means denoising algorithm is designed and defined. </LI> <LI> The quantitative evaluation results confirm the feasibility of high-energy industrial X-ray imaging. </LI> </UL> </P>

Highly efficient computer algorithm for identifying layer thickness of atomically thin 2D materials

Lee, Jekwan,Cho, Seungwan,Park, Soohyun,Bae, Hyemin,Noh, Minji,Kim, Beom,In, Chihun,Yang, Seunghoon,Lee, Sooun,Seo, Seung Young,Kim, Jehyun,Lee, Chul-Ho,Shim, Woo-Young,Jo, Moon-Ho,Kim, Dohun,Choi, Hy IOP 2018 Journal of Physics. D, Applied Physics Vol.51 No.11

<P>The fields of layered material research, such as transition-metal dichalcogenides (TMDs), have demonstrated that the optical, electrical and mechanical properties strongly depend on the layer number <I>N</I>. Thus, efficient and accurate determination of <I>N</I> is the most crucial step before the associated device fabrication. An existing experimental technique using an optical microscope is the most widely used one to identify <I>N</I>. However, a critical drawback of this approach is that it relies on extensive laboratory experiences to estimate <I>N</I>; it requires a very time-consuming image-searching task assisted by human eyes and secondary measurements such as atomic force microscopy and Raman spectroscopy, which are necessary to ensure <I>N</I>. In this work, we introduce a computer algorithm based on the image analysis of a quantized optical contrast. We show that our algorithm can apply to a wide variety of layered materials, including graphene, MoS<SUB>2</SUB>, and WS<SUB>2</SUB> regardless of substrates. The algorithm largely consists of two parts. First, it sets up an appropriate boundary between target flakes and substrate. Second, to compute <I>N</I>, it automatically calculates the optical contrast using an adaptive RGB estimation process between each target, which results in a matrix with different integer <I>N</I>s and returns a matrix map of <I>N</I>s onto the target flake position. Using a conventional desktop computational power, the time taken to display the final <I>N</I> matrix was 1.8 s on average for the image size of 1280 pixels by 960 pixels and obtained a high accuracy of 90% (six estimation errors among 62 samples) when compared to the other methods. To show the effectiveness of our algorithm, we also apply it to TMD flakes transferred on optically transparent <I>c</I>-axis sapphire substrates and obtain a similar result of the accuracy of 94% (two estimation errors among 34 samples).</P>

Performance evaluation of total variation (TV) denoising technique for dual-energy contrast-enhanced digital mammography (CEDM) with photon counting detector (PCD): Monte Carlo simulation study

Lee, Seungwan,Lee, Youngjin Pergamon 2019 Radiation physics and chemistry Vol.156 No.-

<P><B>Abstract</B></P> <P>The dual-energy contrast-enhanced digital mammography (CEDM) system based on a photon counting detector (PCD) is very useful providing functional information for breast cancer detection. In particular, this system can be used to solve the spectral overlap and high radiation dose problems. However, imaging noise is a big problem because of the degradation image performance and cancer detection ratio in the CEDM system. To address this problem, a total variation (TV)-based denoising technique approach has recently been studied. Thus, the aim of this study was to evaluate and confirm the image performance of our TV-based denoising technique with dual-energy CEDM with a PCD. For this purpose, we simulated a dual-energy CEDM with a PCD and breast phantom in Monte Carlo simulation using the Geant4 Application for Tomographic Emission (GATE) that is an essential open source program. We also designed a TV-based denoising technique based on the L<SUB>1</SUB>-norm estimation included correction and iteration steps for acquiring high edge preservation in X-ray images. To evaluate the image performance, we used evaluation parameters with a contrast-to-noise ratio (CNR) and coefficient of variation (COV) as a function of the absorbed dose levels (2.18, 1.53, 1.09, and 0.66 mGy). According to the results, the average of all iodine thicknesses and absorbed dose conditions for the CNR using our proposed TV-based denoising technique was 1.71, 1.39, and 1.13 times higher than that acquired for the noisy image, median filter and Wiener filter, respectively. We also acquired excellent COV results for the dual-energy CEDM with a PCD system (2.53 times higher than that of the noisy image). In conclusion, the results of this study suggested that a TV-based denoising technique can be achieved with an improved image performance and the effect and feasibility of the TV-based denoising technique for dual-energy CEDM with a PCD can be investigated.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Monte Carlo simulation of CZT X-ray imaging system and breast phantom. </LI> <LI> The noise reduction studies have been undertaken on a dual-energy CEDM with a CZT photon counting detector. </LI> <LI> The comparison results using contrast-to-noise ratio and coefficient of variation confirms the noise reduction quality of total variation. </LI> </UL> </P>

Respiratory-correlated 4D digital tomosynthesis with deep convolutional neural networks for image-guided radiation therapy

Lee Seungwan 한국물리학회 2021 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.78 No.2

4D digital tomosynthesis (DTS) techniques for image-guided radiation therapy (IGRT) are able to reduce radiation dose, scan and reconstruction time compared to 4D cone-beam computed tomography (CBCT). In spite of these benefits, the 4D DTS techniques cause the degradation of image quality due to an intrinsic imaging strategy and consequently reduce treatment accuracy. In this study, a deep learning-based convolutional neural network (CNN) framework was proposed for 4D DTS imaging. The proposed CNN framework consisted of the data restoration network based on a U-Net and the denoising network combined with a 2D wavelet transform, and the network training was implemented with clinical images. The quality of the 4D DTS images obtained from the proposed model was evaluated in terms of quantitative accuracy, spatial resolution and noise property. The results showed that the proposed CNN framework improved the quantitative accuracy of 4D DTS images by 3–19%, and the spatial resolution and noise for the proposed CNN framework were reduced by 2.24–7.33% and 8.92–40.07%, respectively, in comparison to other imaging models. These results represented that the degradation of the 4D DTS image quality can be recovered using the proposed CNN framework, and the proposed model is suitable for maintaining spatial resolution as well as suppressing noise and artifacts. In conclusion, the proposed CNN framework can be potentially used to improve the quality of 4D DTS images for the IGRT.

시설원예 국제화를 위한 연구방향 제언

이승완(Seungwan Lee) 한국원예학회 2016 한국원예학회 학술발표요지 Vol.2016 No.10

Review of the impact of the Integration of Smart Meters on the Utility Organization Structure

Jaewon Lee(이제원),Yong Tae Yoon(윤용태),Seungwan Kim(김승완),Young Gyu Jin(진영규),Hyunjoong Kim(김현중),Sehoon Paik(백세훈),Dongsu Lee(이동수),Yongsoon Kim(김용순) 한국신재생에너지학회 2020 한국신재생에너지학회 학술대회논문집 Vol.2020 No.8

Anisotropic Adhesion of Micropillars with Spatula Pads

Seo, Seungwan,Lee, Jehong,Kim, Kwang-Seop,Ko, Kwang Hee,Lee, Jong Hyun,Lee, Jongho American Chemical Society 2014 ACS APPLIED MATERIALS & INTERFACES Vol.6 No.3

<P>Natural gecko adhesive structures consisting of angled setae, branched into thin spatulas, have remarkable properties including easily attachable and releasable anisotropic adhesion. The geometrically asymmetric structures lead to anisotropic adhesive properties. Inspired by the gecko, we fabricated an array of micropillars with asymmetric spatula pads from elastomeric materials. This paper describes the anisotropic properties of the micropillars with spatula pads as established by experimental measurements and observation together with finite element analysis. The results indicate that the structural difference of the spatula pad at one edge of the micropillar provides the anisotropic adhesive properties.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/aamick/2014/aamick.2014.6.issue-3/am4044135/production/images/medium/am-2013-044135_0005.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/am4044135'>ACS Electronic Supporting Info</A></P>

태충의 해부학적 구조와 효율적인 자침법에 관한 연구

Yu Seungwan,Lee Wonhee,Kim Suhyun,Park Seyeon,Lee Eunhye,Huh Jinseok,Kim Hongik,Jung Sehun,Chu Hongmin 대한침도의학회 2023 대한침도의학회지 Vol.7 No.2

Background: The aim of this study is to provide the anatomical information and physi- ological effect of LR3 with its needling depth and retention time. Methods: We investigated the information of LR3 from literature and related research. Then we searched the clinical effect and needling depth, angle, retention time of LR3 from on-line databases like ‘DBPIA’, ‘KISS’, ‘OASIS’, ‘RISS’, PUBMED’ and ‘Google Scholar’ (2005-2023). Results: The needling depth of LR3 is 7-13 mm in the classic test, that of contemporary re- search is 10-20 mm. When stimulating LR3, the relative anatomical structures are dorsalis pedis artery and medial terminal branch of deep peroneal nerve. Conclusion: The effect of LR3 is originated from stimulation of deep peroneal nerve near- by dorsalis pedis artery. It activates the parasympathetic nerve through the induction of somatic autonomous reflex which leads to the effect of blood vessel expansion, intestinal movement activation, and blood sugar drop.

Effect of Unmatched System Models on Iterative Reconstruction in Computed Tomography: A Phantom Study

Youngjin Lee,Seungwan Lee 한국물리학회 2020 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.76 No.9

System models used for iterative reconstruction affect the quality of computed tomography (CT) images. The imaging performance of the system models depends on the projectors, which implements forward- and back-projection. The system model based on a single projector is limited to improve image quality because each projector has both benefits and drawbacks. In this study, the effect of unmatched system models on iterative reconstruction was investigated by evaluating the image quality of reconstructed images. The unmatched system models composed of different projectors were used to perform iterative reconstruction. The image quality was evaluated in order to investigate the effect of the unmatched system models, and the imaging performance of the unmatched system models was compared with that of the matched system models by simulations and experiments with digital and anthropomorphic head phantoms. The results showed that the characteristics of CT images depended on the combinations of forward- and back-projectors, and the unmatched system models are able to improve the quality of the images obtained by using iterative reconstruction. The unmatched system models can be potentially used to improve the imaging performance of iterative reconstruction in CT systems.