• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.178-186
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• 2009

The quality control is needed to ensure the accuracy of medical information and achieved by evaluating the performance of and maintaining the system and practicing various measurements and evaluations. The Korean Institute for Accreditation of Medical Image, therefore, have held educational program for quality control of special medical equipments. The major of programs participants, however, are radiology specialists with only small number of radiological technologists from some hospitals, furthermore, the follow-up education and the share of information between participants and non-participants are insufficient in general, thus, the knowledge level of radiological technologists, regardless of their participation, is relatively low. This study carried out the questionnaire research for the 500 radiological technologists registered in Korean Society of MRI Technology, on the basis of 2008, and performed analysis for five months from May to Oct., 2008. The questionnaires were delivered by post to each radiological technologists and the response rate was 36%(n=180). The results of this revealed that the 86.7% of respondents felt the necessity of inspection on quality management, while only the 27.8% completed the educational program for manager of special medical equipment. and only the half(53.9%) had the knowledge about inspection on quality management. The completion of educational program had no correlations with sex, age, size of occupying hospital, the number of radiological technologists in occupying site and MRI laboratory, career year of general radiologist and in MRI laboratory, and the presence of biomedical engineering department in occupying hospital. The 78.0% of participants at the educational program for quality management held by the Korean Institute for Accreditation of Medical Image had the knowledge about inspection on quality management(p<.05) whereas the 43.9% of the hospitals held such program and the 54.4% of radiological technologists from those hospitals had related knowledge, which indicated that such programs held by hospitals had not effects on the knowledge level of radiological technologists. This indicates also that the contents, methods, and other conditional factors of educational programs are important for the outcome of them.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.1
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• pp.47-51
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• 2016

Purpose By ingestion of 18F-FDG of kidney of PET/CT during the inspection, if additional examination is required, depending on whether you want to water intake, we want to confirm a change in the rate of decrease of F-18 FDG of the kidney. Materials and Methods The 80 patients without kidney disease were performed PET/CT examination. Device was analyzed after setting the kidney to a three-dimensional region of interest. In patients require additional examination, and inspection after 30 minutes, a PET/CT torso examination after the water of the 500 cc ingested at a time. After the addition of both water intake group and no hydration group of kidney of SUV, it was compared with PET/CT torso scan. Results High and low of the kidney SUV did not show a significant difference in the rate of decrease. Reduction rates of background (BKG) of additional examination was 2.8% and reduction rates of SUV was 49.7% (Hydration) : -6.8% (No hydration), so did show a significant difference. In the image blind test, the average point score of hydration and no hydration was 34.25 : 17.25. Conclusion An undercurrent of 18F-FDG in the kidney at the time of torso examination, it was confirmed that the reduction rate after the addition of water intake is high. It is considered that can be expected to improve the quality of an image due to a decrease in elongation through the kidneys examination with additional fluid intake as needed intake.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.11-20
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• 2022

The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.219-224
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• 2011

To improve medical service and customers' satisfaction by reducing actual waiting time for medical inspection by personalized examination guidance contents (PEGC) linked with medical information system (MIS). The suggested PEGC was completed with preparing transmission for data and PEGC by using transmission control protocol internet protocol (TCP/IP) which can be built up creditable data transmission service. When patient signal event appeared in MIS while the communication was in standby, the ID and data of the customer were shown as text and image on monitors in waiting room. Guiding inspections, steps of examination, and undressing information extracted from the PEGC was also shown to the appropriate patient. After installation of the suggested PEGC, we rechecked satisfaction rates of 60 customers who visited the hospital with a same method as initial survey. The results of this study suggest that 3.6 point of waiting time satisfaction index were improved, after installation of the suggested PEGC, as 4.6 point.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.271-278
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• 2014

In spite of that stop line and crosswalk should be aware of the most basic objects in transportation system, its features extracted are very limited. In addition to image-based recognition technology, laser and RF, GPS/INS recognition technology, it is difficult to recognize. For this reason, the limited research in this area has been done. In this paper, the algorithm to recognize the stop line and crosswalk is designed and implemented using image-based recognition technology with the images input through a vision sensor. This algorithm consists of three functions.; One is to select the area, in advance, needed for feature extraction in order to speed up the data processing, 'Region of Interest', another is to process the images only that white color is detected more than a certain proportion in order to remove the unnecessary operation, 'Color Pattern Inspection', the other is 'Feature Extraction and Recognition', which is to extract the edge features and compare this to the previously-modeled one to identify the stop line and crosswalk. For this, especially by using case based feature comparison algorithm, it can identify either both stop line and crosswalk exist or just one exists. Also the proposed algorithm is to develop existing researches by comparing and analysing effect of in-vehicle camera installation and changes in recognition rate of distance estimation and various constraints such as backlight and shadow.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.98-106
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• 2024

Due to advancements in construction technology and analytical tools, an increasing number of cable-stayed bridges have been designed and constructed in recent years. A cable is a structural element that primarily transmits the main load of a cable-stayed bridge and plays the most crucial role in reflecting the overall condition of the entire bridge system. In this study, a vision-based method was applied to estimate the tension of the stay cables located at a long distance. To measure the response of a cable using a vision-based method, it is necessary to install feature points or targets on the cable. However, depending on the location of the point to be measured, there may be no feature points in the cable, and there may also be limitations in installing the target on the cable. Hence, it is necessary to find a way to measure cable response that overcomes the limitations of existing vision-based methods. This study proposes a method for measuring cable responses by utilizing the characteristics of cable shape. The proposed method involved extracting the cable shape from the acquired image and determining the center of the extracted cable shape to measure the cable response. The extracted natural frequencies of the vibration mode were obtained using the measured responses, and the tension was estimated by applying them to the vibration method. To verify the reliability of the vision-based method, cable images were obtained from the Hwatae Bridge in service under ambient vibration conditions. The reliability of the method proposed in this study was confirmed by applying it to the vibration method using a vision-based approach, resulting in estimated tensions with an error of less than 1% compared to tensions estimated using an accelerometer.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.29-38
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• 2005

Even though underground conduits have became important city-infra structures which should be exhaustively and efficiently managed, there is few systems which supports the well-defined facility management standards. Due to the lack of the supporting systems, experts must visit underground conduits scattered several cities over the country to see and check the status of the underground conduits including built-in facilities. This type of management gives us a little bit delayed status information at the end of so much time and money costs. In this paper, to solve this problem and manage the conduit synthetically, we developed a web-based facility management system for underground conduits by using information technologies. The developed management system has a simplified map drawing interface to depict the overall architectures and locations of underground conduits and their built-in facilities into sketch maps. And, the system uses the 3D panorama image technology with zooming functions in addition to still images and video images to give the feeling of a spot inspection. Moreover, since the system accumulates the data of repair/reinforcement, occasional inspections and safety diagnosis, conduit managers can synthetically and effectively manage the facilities within underground conduits and themselves.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.887-895
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• 2013

Metastatic bone cancer, the cancer which occurred in the various organs and progressively spread to bone, is one of the complications in cancer patients. This cancer is divided into the osteoblast and osteolytic metastasis. Although Computer Tomography(CT) could be an useful tool in diagnosis of bone metastasis, lesions are often missed by the visual inspection and it makes clinicians difficult to detect metastasis earlier. Therefore, in this study, we construct a three-dimensional(3D) volume rendering data from tomography images of the chest CT, and apply a 3D based image processing algorithm to them for detection bone metastasis lesions. Then we perform a three-dimensional visualization of the detected lesions.From our test using 10 clinical cases, we confirmed 94.1% of average sensitivity for osteoblast, and 90.0% of average sensitivity, respectively. Consequently, our findings showed a promising possibility and potential usefulness in diagnosis of metastastic bone cancer.