• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.67-67
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• 2003

It is crucial to minimize setup errors of a cancer treatment machine using a high energy and to perform precise radiation therapy. Usually, port film has been used for verifying errors. The Korea Cancer Center Hospital (KCCH) has manufactured digital electronic portal imaging device (EPID) system to verify treatment machine errors as a Quality Assurance (Q.A) tool. This EPID was consisted of a metal/fluorescent screen, 45$^{\circ}$ mirror, a camera and an image grabber and could display the portal image with near real time KIRAMS has also made the acrylic phantom that has lead line of 1mm width for ligh/radiation field congruence verification and reference points phantom for using as an isocenter on portal image. We acquired portal images of 10$\times$10cm field size with this phantom by EPID and portal film rotating treatment head by 0.3$^{\circ}$, 0.6$^{\circ}$ and 0.9$^{\circ}$. To check field size, we acquired portal images with 18$\times$18cm, 19$\times$19cm and 20$\times$20cm field size with collimator angle 0$^{\circ}$ and 0.5$^{\circ}$ individually. We have performed Flatness comparison by displaying the line intensity from EPID and film images. The 0.6$^{\circ}$ shift of collimator angle was easily observed by edge detection of irradiated field size on EPID image. To the extent of one pixel (0.76mm) difference could be detected. We also have measured field size by finding optimal threshold value, finding isocenter, finding field edge and gauging distance between isocenter and edge. This EPID system could be used as a Q.A tool for checking field size, light/radiation congruence and flatness with a developed video based EPID.

• Journal of the Korean Geotechnical Society
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• v.23 no.7
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• pp.5-16
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• 2007

The monitoring and investigation of underwater landslide help to understand its mechanism, increase the usefuless of design and construction and reduce the losses. This paper presents three high resolution geophysical techniques electrical resisitance, ultrasonic wave reflection imaging, and shear wave tomography conducted to determine the lab-scaled submerged landslide. Electrical resistance profiles of a soil mass obtained by an electrical resistance probe provide detailed information to assess the spatial distribution of the soil mass with milimetric resolution. An ultrasonic wave image obtained by recording the reflections from interfaces of different impedance materials permits detecting layers and landslide with submilimetric resolution. The pixel based image of immersed landslides is created by the inversion of the boundary information achieved from the traveling time of shear waves. The experimental results show that the ultrasonic wave imaging and the electrical resistance can provide complementary information; and their association with S-wave tomography image can produce a 3-D view of the underwater landslide. This study suggests that geophysical techniques may be effective tools for the detection of the underwater landslides and spatial distribution offshore.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.843-849
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• 2023

This study attempted to determine the optimal algorithm after quantitatively analyzing noise, SNR, and CNR measurements by reconstructing four algorithms (Standard, Soft, Bone, and Detail) from head and neck CT images of patients who underwent implant surgery. As an analysis method, pixel values were calculated through the region of interest in the reconstructed image using the Image J program. For noise, SNR, and CNR, the region of interest was measured at the location of the pharynx, masseter muscle, and parotid gland in the image, and the mean and SD values were obtained. The values of SNR and CNR were calculated based on the given formula. As a result, the standard algorithm showed the lowest noise and the highest SNR. CNR was highest in the Soft algorithm, but showed no significant difference from the Standard algorithm. Therefore, it is believed that the Standard algorithm is the optimal algorithm for examining patients wearing intraoral implants in head and neck CT examinations. We hope that the data from this study will be used as basic data for image evaluation in head and neck CT examinations, and that the quality of images will be further improved through various algorithm changes. It is believed that this will be an opportunity to do so.

• Information Systems Review
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• v.25 no.1
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• pp.129-143
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• 2023

In the era of big data, the field of artificial intelligence is showing remarkable growth, and in particular, the image classification learning methods by deep learning are becoming an important area. Various studies have been actively conducted to further improve the performance of CNNs, which have been widely used in image classification, among which a representative method is the Convolutional Recurrent Neural Network (CRNN) algorithm. The CRNN algorithm consists of a combination of CNN for image classification and RNNs for recognizing time series elements. However, since the inputs used in the RNN area of CRNN are the flatten values extracted by applying the convolution and pooling technique to the image, pixel values in the same phase in the image appear in different order. And this makes it difficult to properly learn the sequence of arrangements in the image intended by the RNN. Therefore, this study aims to improve image classification performance by proposing a novel hybrid method of CNN and RNN applying the concepts of encoder and decoder. In this study, the effectiveness of the new hybrid method was verified through various experiments. This study has academic implications in that it broadens the applicability of encoder and decoder concepts, and the proposed method has advantages in terms of model learning time and infrastructure construction costs as it does not significantly increase complexity compared to conventional hybrid methods. In addition, this study has practical implications in that it presents the possibility of improving the quality of services provided in various fields that require accurate image classification.

• Progress in Medical Physics
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• v.26 no.4
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• pp.215-222
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• 2015

In this work, we performed a proof-of-concept experiment for phase-contrast x-ray imaging (PCXI) based on a single antiscatter grid and a polychromatic x-ray source. We established a table-top setup which consists of a focused-linear grid having a strip density of 200 lines/inch, a microfocus x-ray tube having a focal-spot size of about $5{\mu}m$, and a CMOS-type flat-panel detector having a pixel size of $48{\mu}m$. By using our prototype PCXI system and the Fourier demodulation technique, we successfully obtained attenuation, scattering, and differential phase-contrast images of improved visibility from the raw images of several selected samples at x-ray tube conditions of $90kV_p$ and 0.1 mAs. Further, fusion image (e.g., the attenuation+the scattering) may have an advantage in displaying details of the sample's structures that are not clearly visible in the conventional attenuation image. Our experimental results indicate that single-grid-based approach seems a useful method for PCXI with great simplicity and minimal requirements on the setup alignment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.69-78
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• 2011

Rice is one of the world's staple foods. Paddy rice fields have unique biophysical characteristics that the rice is grown on flooded soils unlike other crops. Information on the spatial distribution of paddy fields and the timing of irrigation are of importance to determine hydrological balance and efficiency of water resource management. In this paper, we detected the timing of irrigation and spatial distribution of paddy fields using the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Aqua satellite. The timing of irrigation was detected by the combined use of MODIS-based vegetation index and Land Surface Water Index (LSWI). The detected timing of irrigation showed good agreement with field observations from two flux sites in Korea and Japan. Based on the irrigation detection, a land cover map of paddy fields was generated with subsidiary information on seasonal patterns of MODIS enhanced vegetation index (EVI). When the MODISbased paddy field map was compared with a land cover map from the Ministry of Environment, Korea, it overestimated the regions with large paddies but underestimated those with small and fragmented paddies. Potential reasons for such spatial discrepancies may be attributed to coarse pixel resolution (500 m) of MODIS images, uncertainty in parameterization of threshold values for discarding forest and water pixels, and the application of LSWI threshold value developed for paddy fields in China. Nevertheless, this study showed that an improved utilization of seasonal patterns of MODIS vegetation and water-related indices could be applied in water resource management and enhanced estimation of evapotranspiration from paddy fields.

• Journal of radiological science and technology
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• v.37 no.2
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• pp.93-100
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• 2014

Recently the development of portable digital wireless imaging system, which acquires digital radiation images by using wireless LAN telecommunications function in an easy and fast way, provides lots of convenience for people. Considering the characteristics of portable imaging tests on emergency and critical patients, this study aims to suggest guidelines for Digital wireless detector by evaluating the effect of de-centering of focus-grid and displacement of subject in detector on the quality of image. The equipments used for this study were Elmo-T6 Digital Mobile X-ray system (SIMAZU Corp.), el' Tor ($14{\times}17$ "Wireless detector), Grid (10:1) and Chest & head phantom. After acquiring post-processing image according to dose increase and de-centering image of grid-focus and head phantom displacement image, this study compared, analyzed and evaluated these images by using a digital image analysis program by Image J. In the change of images based on dose increase, images were rough in the dose of 0.5 mAs, while there was no difference among images in the proper dose of 1~2 mAs and, especially from 2.5 mAs, average value of pixels radically decreased, affecting contrast. Over 3 mAs, contrast dropped due to saturation phenomenon of lungs. As the result of analysis using Image J program, with the increase of displacement between focus-grid and head phantom, the frequency of low pixel value also increase, causing the outline of surface image to disappear, which in turn affects contrast. For better quality imaging, a radiographer must be aware before the time of test that the image quality can be changed based on the critical patient's posture, movement, respiration, displacement of X-ray tube and distance of imaging.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Progress in Medical Physics
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• v.23 no.2
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• pp.91-98
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• 2012

Verification of internal organ motion during treatment and its feedback is essential to accurate dose delivery to the moving target. We developed an offline based internal organ motion verification system (IMVS) using cine EPID images and evaluated its accuracy and availability through phantom study. For verification of organ motion using live cine EPID images, a pattern matching algorithm using an internal surrogate, which is very distinguishable and represents organ motion in the treatment field, like diaphragm, was employed in the self-developed analysis software. For the system performance test, we developed a linear motion phantom, which consists of a human body shaped phantom with a fake tumor in the lung, linear motion cart, and control software. The phantom was operated with a motion of 2 cm at 4 sec per cycle and cine EPID images were obtained at a rate of 3.3 and 6.6 frames per sec (2 MU/frame) with $1,024{\times}768$ pixel counts in a linear accelerator (10 MVX). Organ motion of the target was tracked using self-developed analysis software. Results were compared with planned data of the motion phantom and data from the video image based tracking system (RPM, Varian, USA) using an external surrogate in order to evaluate its accuracy. For quantitative analysis, we analyzed correlation between two data sets in terms of average cycle (peak to peak), amplitude, and pattern (RMS, root mean square) of motion. Averages for the cycle of motion from IMVS and RPM system were $3.98{\pm}0.11$ (IMVS 3.3 fps), $4.005{\pm}0.001$ (IMVS 6.6 fps), and $3.95{\pm}0.02$ (RPM), respectively, and showed good agreement on real value (4 sec/cycle). Average of the amplitude of motion tracked by our system showed $1.85{\pm}0.02$ cm (3.3 fps) and $1.94{\pm}0.02$ cm (6.6 fps) as showed a slightly different value, 0.15 (7.5% error) and 0.06 (3% error) cm, respectively, compared with the actual value (2 cm), due to time resolution for image acquisition. In analysis of pattern of motion, the value of the RMS from the cine EPID image in 3.3 fps (0.1044) grew slightly compared with data from 6.6 fps (0.0480). The organ motion verification system using sequential cine EPID images with an internal surrogate showed good representation of its motion within 3% error in a preliminary phantom study. The system can be implemented for clinical purposes, which include organ motion verification during treatment, compared with 4D treatment planning data, and its feedback for accurate dose delivery to the moving target.