• Ocean and Polar Research
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• v.31 no.4
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• pp.415-422
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• 2009

The wave observation system in Korea has been established with an emphasis on pointmeasurement based on in situ instrumentations. However, the system cannot fully investigate the coastal wave-related problems that are significantly localized and intensified with three-dimensional regional geometries. Observation technique that can cover local processes with large time and spatial variation needs to be established. Video imaging techniques that can provide continuous monitoring of coastal waves and related phenomena with high spatial and temporal resolutions at minimum cost of instrumentation risks are reviewed together with present status of implementation in Korea. Practical applications of the video imaging techniques are suggested to tackle with various coastal issues of public concern in Korea including, real-time monitoring of wave runup and overtopping of swells on the east coast of Korea, longshore and rip currents, morphological and bathymetric changes, storm surge and tsunami inundation, and abnormal extreme waves in the west coast of Korea, etc.

• Proceedings of the Optical Society of Korea Conference
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• 2005.07a
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• pp.94-95
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• 2005

• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.281-282
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• 2008

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.796-804
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• 1994

This paper presents Inverse SAR imaging algorithm for a unknown velocity target and a real ISAR data is processed and applied to the algorithm. The real ISAR data is obtained by transmitting a number of pulse modulated by a stepped-frequency method and the received data are undersampled. We present a method applicable for the case of a undersampled data base. In this method, the original echoed signal is mixed with a reference signal to make it unaliased, followed by being interpolated. Target`s velocity required for the algorithm is estimated via subaperture processing and after the coordinate transformation into squint-mode SAR with the estimated velocity, a recently proposed SAR/ISAR imaging algorithm derived without any approximation is utilized to produce the output image. We also propose an ISAR image scheme that is usable when a target changes its velocity during ISAR data acquisition time.

• Journal of the Optical Society of Korea
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• v.15 no.4
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• pp.386-393
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• 2011

In this study, we report an effective k-domain linearization method with a pre-calibrated indexed look-up table. The method minimizes k-domain nonlinear characteristics of a swept source optical coherence tomography (SS-OCT) system by using two arrays, a sample position shift index and an intensity compensation array. Two arrays are generated from an interference pattern acquired by connecting a Fabry-Perot interferometer (FPI) and an optical spectrum analyzer (OSA) to the system. At real time imaging, the sample position is modified by location movement and intensity compensation with two arrays for linearity of wavenumber. As a result of evaluating point spread functions (PSFs), the signal to noise ratio (SNR) is increased by 9.7 dB. When applied to infrared (IR) sensing card imaging, the SNR is increased by 1.29 dB and the contrast noise ratio (CNR) value is increased by 1.44. The time required for the linearization and intensity compensation is 30 ms for a multi thread method using a central processing unit (CPU) compared to 0.8 ms for compute unified device architecture (CUDA) processing using a graphics processing unit (GPU). We verified that our linearization method is appropriate for applying real time imaging of SS-OCT.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.395-398
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• 2002

Many research group started study to develope x-ray detector using thin film transistor from 1970. But realization of TFT based x-ray detector development was caused by progress of thin film transistor liquid crystal display(TFTLCD) device technology in 1990. The main current of TFT technology is display device. Research results expend TFT technology field from display device to sensor manufacture technology. These days many research group in the world realize various digital x-ray detector. In this study, We compare discharge erasing method to visible light erasing method in a-Se based digital x-ray detector. Visible light erasing method is known reset process in direct conversion x-ray detector. Digital x-ray detector using visible light erasing method is not adaptive for conventional x-ray device, because of its thickness. And it is not avaliable for real-time imaging for digital fluoroscopy, because of its long reset time. In this study we overcome these limitations and show new idea for real-time imaging method.

• Journal of IKEEE
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• v.26 no.1
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• pp.27-35
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• 2022

This paper proposes an ultrasound vessel-pattern imaging algorithm with low computational complexity. The proposed imaging algorithm reconstructs blood-vessel patterns by only detecting blood flow, and can be applied to a real-time signal processing hardware that extracts an ultrasonic finger-vessel pattern. Unlike a blood-flow imaging mode of typical ultrasound medical imaging device, the proposed imaging algorithm only reconstructs a presence of blood flow as an image. That is, since the proposed algorithm does not use an I/Q demodulation and detects a presence of blood flow by accumulating an absolute value of the clutter-filter output, a structure of the algorithm is relatively simple. To verify a complexity of the proposed algorithm, a simulation model for finger vessel was implemented using Field-II program. Through the behavioral simulation, it was confirmed that the processing time of the proposed algorithm is around 54 times less than that of the typical color-flow mode. Considering the required main building blocks and the amount of computation, the proposed algorithm is simple to implement in hardware such as an FPGA and an ASIC.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1213-1224
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• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

• Journal of Microbiology and Biotechnology
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• v.25 no.10
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• pp.1728-1733
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• 2015

This study was done to establish a mouse model for catheter-related biofilm infection suitable to bioluminescence imaging (BLI). Biofilm formation of Pseudomonas aeruginosa (P. aeruginosa) Xen5 grown on catheter disks in vitro and in an implanted mouse model was real-time monitored during a 7-day study period using BLI. The numbers of integrated brightness (IB) and viable bacterial count (VBC) in the biofilm disks in vitro were highest at 24 h after inoculation; the IB of biofilm in vivo was increased until 24 h after implantation. A statistical correlation was observed between IB and VBC in vitro by linear regression analysis. The actual VBC value in vivo can be estimated accurately by IB without sacrifice. In addition, we monitored the change in white blood cells (WBCs) during infection. The number of WBCs on day 7 was significantly higher in the infection group than in the control group. This study indicates that BLI is a simple, fast, and sensitive method to measure catheter biofilm infection in mice.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1044-1052
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• 2010

In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.