• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.133-137
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• 2010

Purpose: Breast cancer is known to be more vulnerable to bone metastasis and lymph node metastasis than other types of cancer, and nuclear examinations whole body bone scan and lymphoscintigraphy are performed commonly before and after breast cancer operation. In case whole body bone scan is performed on the day before lymphoscintigraphy, the radiopharmaceutical taken into and remaining in the bones provides anatomical information for tracking and locating sentinel lymph nodes. Thus, this study purposed to examine how much bone density affects in locating sentinel lymph nodes. Materials and Methods: The subjects of this study were 22 patients (average age $52{\pm}7.2$) who had whole body bone scan and lymphoscintigraphy over two days in our hospital during the period from January to December, 2009. In the blind test, 22 patients (average age $57{\pm}6.5$) who had lymphoscintigraphy using $^{57}Co$ flood phantom were used as a control group. In quantitative analysis, the relative ratio of the background to sentinel lymph nodes was measured by drawing ROIs on sentinel lymph nodes and the background, and in gross examination, each of a nuclear physician and a radiological technologist with five years' or longer field experience examined images through blind test in a five-point scale. Results: In the results of quantitative analysis, the relative ratio of the background to sentinel lymph nodes was 14.2:1 maximum and 8.5:1 ($SD{\pm}3.48$) on the average on the front, and 14.7:1 maximum and 8.5:1 ($SD{\pm}3.42$) on the average on the side. In the results of gross examination, when $^{57}Co$ flood phantom images were compared with images containing bones, the score was relative high as 3.86 ($SD{\pm}0.35$) point for $^{57}Co$ flood phantom images and 4.09 ($SD{\pm}0.42$) for bone images. Conclusion: When whole body bone scan was performed on the day before lymphoscintigraphy, the ratio of the background to sentinel lymph nodes was over 10:1, so there was no problem in locating lymph nodes. In addition, we expect to reduce examination procedures and improve the quality of images by indicating the location of sentinel lymph nodes using bone images as body contour without the use of a source.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1099-1110
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• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Korean Journal of Environment and Ecology
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• v.26 no.3
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• pp.322-332
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• 2012

The objectives of this paper were to investigate home range, habitat selection, and threat factors of leopard cats (Prionailurus bengalensis) living in rural area of Korea. The results based on radio tracking of three leopard cats (two males and one female) can be summarized as follows. First, the average home range of leopard cats were $2.64{\pm}1.99km^2$ (Kernel 95) and $3.69{\pm}1.34km^2$ (MCP 100), and the average size of core areas was $0.64{\pm}0.47km^2$ (Kernel 50). The home range of a male leopard cat that radio-tracked in winter was the largest ($5.19km^2$, MCP 100). Second, the Johnson's habitat selection model based on the Jacobs index showed that leopard cats preferred meadows and paddy fields avoiding forest covers at the second level, whereas they preferred meadows adjacent to streams and avoided paddy fields at the third level. Finally, roadkill could be prime threat factor for the cat population. Therefore, habitats dominated by paddy fields, stream corridors with paved roads, and human settlements with insufficient forest patches could threaten the long-term viability of leopard cat populations. Thus the habitat managements for the leopard cat conservation should focus on the prevention of road-kill and the installation of wildlife passages in rural highways adjacent to stream corridors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.685-691
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• 2020

In this study, an algorithm that recognizes numbers from 0 to 9 was developed using the data obtained after tracking hand movements using the echo signal of a millimeter-wave radar sensor at 77 GHz. The echo signals obtained from the radar sensor by detecting the motion of a hand gesture revealed a cluster of irregular dots due to the difference in scattering cross-sectional area. A valid center point was obtained from them by applying a K-Means algorithm using 3D coordinate values. In addition, the obtained center points were connected to produce a numeric image. The recognition rate was compared by inputting the obtained image and an image similar to human handwriting by applying the smoothing technique to a CNN (Convolutional Neural Network) model trained with MNIST (Modified National Institute of Standards and Technology database). The experiment was conducted in two ways. First, in the recognition experiments using images with and without smoothing, average recognition rates of 77.0% and 81.0% were obtained, respectively. In the experiment of the CNN model with augmentation of learning data, a recognition rate of 97.5% and 99.0% on average was obtained in the recognition experiment using the image with and without smoothing technique, respectively. This study can be applied to various non-contact recognition technologies using radar sensors.

• Progress in Medical Physics
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• v.29 no.1
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• pp.8-15
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• 2018

This work reports the acceptance testing and commissioning experience of the Robotic Intensity-Modulated Radiation Therapy (IMRT) M6 system with a newly released $InCise^{TM}2$ Multileaf Collimator (MLC) installed at the Yonsei Cancer Center. Acceptance testing included a mechanical interdigitation test, leaf positional accuracy, leakage check, and End-to-End (E2E) tests. Beam data measurements included tissue-phantom ratios (TPRs), off-center ratios (OCRs), output factors collected at 11 field sizes (the smallest field size was $7.6mm{\times}7.7mm$ and largest field size was $115.0mm{\times}100.1mm$ at 800 mm source-to-axis distance), and open beam profiles. The beam model was verified by checking patient-specific quality assurance (QA) in four fiducial-inserted phantoms, using 10 intracranial and extracranial patient plans. All measurements for acceptance testing satisfied manufacturing specifications. Mean leaf position offsets using the Garden Fence test were found to be $0.01{\pm}0.06mm$ and $0.07{\pm}0.05mm$ for X1 and X2 leaf banks, respectively. Maximum and average leaf leakages were 0.20% and 0.18%, respectively. E2E tests for five tracking modes showed 0.26 mm (6D Skull), 0.3 mm (Fiducial), 0.26 mm (Xsight Spine), 0.62 mm (Xsight Lung), and 0.6 mm (Synchrony). TPRs, OCRs, output factors, and open beams measured under various conditions agreed with composite data provided from the manufacturer to within 2%. Patient-specific QA results were evaluated in two ways. Point dose measurements with an ion chamber were all within the 5% absolute-dose agreement, and relative-dose measurements using an array ion chamber detector all satisfied the 3%/3 mm gamma criterion for more than 90% of the measurement points. The Robotic IMRT M6 system equipped with the $InCise^{TM}2$ MLC was proven to be accurate and reliable.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.33-47
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• 2022

Wild boars(Sus scrofa) are expanding their range of behavior as their habitats change. Appearing in urban centers and private houses, it caused various social problems, including damage to crops. In order to prevent damage and effectively manage wild boars, there is a need for ecological research considering the characteristics and movement characteristics of wild boars. The purpose of this study is to analyze home range and identify land cover types in key areas through tracking wild boars, and to predict the movement connectivity of wild boars in consideration of previous studies and their preferred land use characteristics. In this study, from January to June 2021, four wild boars were captured and tracked in Jinju city, Gyeongsangnam-do, and the preferred land cover type of wild boars was identified based on the MCP 100%, KDE 95%, and KDE 50% results. As a result of the analysis of the home range for each individual, it was found that 100% of MCP was about 0.68km², 2.77km², 2.42km², and 0.16km², and the three individuals overlapped the home range, refraining from habitat movement and staying in the preferred area. The core areas were analyzed as about 0.55km², 2.05km², 0.82km², and 0.14km² with KDE 95%., and about 0.011km², 0.033km², 0.004km², and 0.003km² with KDE 50%. When the preferred land cover type of wild boar was confirmed based on the results of analysis of the total home range area and core area that combined all individuals, forests were 55.49% (MCP 100%), 54.00% (KDE 95%), 77.69% (KDE 50%), respectively, with the highest ratio, and the urbanization area, grassland, and agricultural area were relatively high. A connectivity scenario was constructed in which the ratio of the land cover type preferred by the analyzed wild boar was reflected as a weight for the resistance value of the connectivity analysis, and this was compared with the connectivity evaluation results analyzed based on previous studies and wild boar characteristics. When the current density values for the wild boar movement data were compared, the average value of the existing scenario was 2.76, the minimum 1.12, and the maximum 4.36, and the weighted scenario had an average value of 2.84, the minimum 0.96, and the maximum 4.65. It was confirmed that, on average, the probability of movement predictability was about 2.90% better even though the weighted scenario had movement restrictions due to large resistance values. It is expected that the identification of the movement route through the movement connectivity analysis of wild boars can be suggested as an alternative to prevent damage by predicting the point of appearance. In the future, when analyzing the connectivity of species including wild boar, it is judged that it will be effective to use movement data on actual species.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.37-43
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• 2013

Purpose: PET/CT scan using the SUV (Standardized Uptake Value) of radiopharmaceutical uptake in organs and tissues as an objective indicator makes it possible to analyze physiological and chemical reactions of human organs. This study analyzes the change of the SUV uptake in accordance with the way how PET/CT patients take a rest after the injection of $^{18}F-FDG$ (Fluororo-deoxyglucose). And also subjective satisfaction is assessed listening to music while taking a rest. Materials and Methods: From April 2011 until February 2013, Among the Primary cancer patients who admitted to the Catholic Medical Center (Seoul & Bucheon St. Mary's Hospital) and scanned $^{18}F-FDG$ PET/CT and also received care through the tracking test (mean age $55.61{\pm}12.41$ years, 108 people, 48 men and 60 women) were selected. The patients were divided into two groups. The first group (A: basal study) is requested to take a rest in bed quietly after the injection. However the second one (B: follow up study) is requested to listen to the music while taking a rest. And then SUV analysis was performed respectively. At the end of the scan, ROI (Region Of Interest) were set from the center of the liver (right lobe) and 3 spots of the brain (frontal, temporal, and occipital lobes). And the SUV was calculated. To identify the correlation among those ROIs, paired t-test was performed using SPSS software (Version 12.0K for windows, P>0.05). Also, after the PET/CT scan the satisfaction study was conducted of all the patients. 1:1 questionnaire survey was performed, and that questionnaire was made using the Likert 5-point scale. By utilizing those questionnaires, the analysis about simple frequency, percentage, average, and standard deviation was performed. Results: The SUV change of the 4 designated ROIs in accordance with listening to music was not statistically significant. (Frontal lobe P-value=0.611, Occipital lobe P-value=0.499, Temporal lobe P-value=0.717, Liver P-value=0.334: P-value>0.05) And the satisfaction study indicated that group B was appear to be 0.42 points (5 basis points) higher than group A. It showed that patients are more satisfied in group B than group A. Conclusion: when performing PET/CT scan using $^{18}F-FDG$, listening to music after the injection of the radiopharmaceuticals does not affect the SUV but given the state of the psychological comfort that may increase the patient's satisfaction.