• Investigative Magnetic Resonance Imaging
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• v.21 no.4
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• pp.233-241
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• 2017

Purpose: To report on the current practices in breast magnetic resonance imaging (MRI) in Korea. Materials and Methods: We invited the 68 members of the Korean Society of Breast Imaging who were working in hospitals with available breast MRI to participate in a survey on how they performed and interpreted breast MRI. We asked one member from each hospital to respond to the survey. A total of 22 surveys from 22 hospitals were analyzed. Results: Out of 22 hospitals, 13 (59.1%) performed at least 300 breast MRI examinations per year, and 5 out of 22 (22.7%) performed > 1200 per year. Out of 31 machines, 14 (45.2%) machines were 1.5-T scanners and 17 (54.8%) were 3.0-T scanners. All hospitals did contrast-enhanced breast MRI. Full-time breast radiologists supervised the performance and interpreted breast MRI in 19 of 22 (86.4%) of hospitals. All hospitals used BI-RADS for MRI interpretation. For computer-aided detection (CAD), 13 (59.1%) hospitals sometimes or always use it and 9 (40.9%) hospitals did not use CAD. Two (9.1%) and twelve (54.5%) hospitals never and rarely interpreted breast MRI without correlating the mammography or ultrasound, respectively. The majority of respondents rarely (13/21, 61.9%) or never (5/21, 23.8%) interpreted breast MRI performed at an outside facility. Of the hospitals performing contrast-enhanced examinations, 15 of 22 (68.2%) did not perform MRI-guided interventional procedures. Conclusion: Breast MRI is extensively performed in Korea. The indication and practical patterns are diverse. The information from this survey would provide the basis for the development of Korean breast MRI practice guidelines.

• Imaging Science in Dentistry
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• v.33 no.3
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• pp.195-198
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• 2003

We present two cases of multiple jaw cysts not associated with basal cell nevus syndrome. Case 1: a nine year-old boy visited CNU Hospital for orthodontic treatment and his radiographs showed cystic lesions surrounding the crowns of teeth #13 and #17 respectively, which were diagnosed as dentigerous cysts. Subsequently, two more cysts were found on his follow-up radiographs in 12 and 15 months. The two cysts were determined to be odontogenic keratocysts. The boy had no skeletal abnormalities and no skin lesions associated with basal cell nevus syndrome. Case 2: a fifty-eight year old man had three impacted third molars with pericoronal radiolucencies, which were diagnosed as dentigerous cysts. He had no additional abnormalities associated with basal cell nevus syndrome. Multiple jaw cysts can occur at any age, and periodic radiographic surveillance may be needed for any cases of impacted tooth.

• Journal of Korean Neurosurgical Society
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• v.64 no.3
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• pp.406-413
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• 2021

Sacrococcygeal teratoma (SCT) is an extragonadal germ cell tumor (GCT) that develops in the fetal and neonatal periods. SCT is a type I GCT in which only teratoma and yolk sac tumors arise from extragonadal sites. SCT is the most common type I GCT and is believed to originate through epigenetic reprogramming of early primordial germ cells migrating from the yolk sac to the gonadal ridges. Fetal SCT diagnosed in utero presents many obstetrical problems. For high-risk fetuses, fetal interventions (devascularization and debulking) are under development. Most patients with SCT are operated on after birth. Complete surgical resection is the key for tumor control, and the anatomical location of the tumor determines the surgical approaches. Incomplete resection and malignant histology are risk factors for recurrence. Approximately 10-15% of patients have a tumor recurrence, which is frequently of malignant histology. Long-term surveillance with monitoring of serum alpha fetoprotein and magnetic resonance imaging is required. Survivors of SCT may suffer anorectal, urological, and sexual sequelae later in their life, and comprehensive evaluation and care are required.

• Korean Journal of Radiology
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• v.24 no.6
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• pp.482-497
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• 2023

Sonazoid, a second-generation ultrasound contrast agent, was introduced for the diagnosis of hepatic nodules. To clarify the issues with Sonazoid contrast-enhanced ultrasonography for the diagnosis of hepatocellular carcinoma (HCC), the Korean Society of Radiology and Korean Society of Abdominal Radiology collaborated on the guidelines. The guidelines are de novo, evidence-based, and selected using an electronic voting system for consensus. These include imaging protocols, diagnostic criteria for HCC, diagnostic value for lesions that are inconclusive on other imaging results, differentiation from non-HCC malignancies, surveillance of HCC, and treatment response after locoregional and systemic treatment for HCC.

• Korean Journal of Radiology
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• v.23 no.11
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• pp.1078-1088
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• 2022

Objective: To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC). Materials and Methods: This retrospective study included 285 patients (mean age ± standard deviation, 62 ± 12 years; 220 male, 77.2%), including 215 for training (n = 161) and internal validation (n = 54) and 70 others for external validation, with newly developed contrast-enhancing lesions at the primary cancer site on the surveillance MRI following definitive treatment of HNSCC between January 2014 and October 2019. Of the 215 and 70 patients, 127 and 34, respectively, had local tumor recurrence. Radiomics models using radiomics scores were created separately for T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and ADC maps using non-zero coefficients from the least absolute shrinkage and selection operator in the training set. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each radiomics score and known clinical parameter (age, sex, and clinical stage) in the internal and external validation sets. Results: Five radiomics features from T2WI, six from CE-T1WI, and nine from ADC maps were selected and used to develop the respective radiomics models. The area under ROC curve (AUROC) of ADC radiomics score was 0.76 (95% confidence interval [CI], 0.62-0.89) and 0.77 (95% CI, 0.65-0.88) in the internal and external validation sets, respectively. These were significantly higher than the AUROC values of T2WI (0.53 [95% CI, 0.40-0.67], p = 0.006), CE-T1WI (0.53 [95% CI, 0.40-0.67], p = 0.012), and clinical parameters (0.53 [95% CI, 0.39-0.67], p = 0.021) in the external validation set. Conclusion: The radiomics model using ADC maps exhibited higher diagnostic performance than those of the radiomics models using T2WI or CE-T1WI and clinical parameters in the diagnosis of local tumor recurrence in HNSCC following definitive treatment.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.345-354
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method has proven to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper, we applied the super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and are overlapped at high rate. We constructed the observation model between the HR images and LR images applied with the Maximum A Posteriori(MAP) reconstruction method which is one of the major methods in the super resolution grid construction. Based on the MAP method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.20-31
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• 2008

In this paper, we propose a single view-based technique for the estimation of human height and position. Conventional techniques for the estimation of 3D geometric information are based on the estimation of geometric cues such as vanishing point and vanishing line. The proposed technique, however, back-projects the image of moving object directly, and estimates the position and the height of the object in 3D space where its coordinate system is designated by a marker. Then, geometric errors are corrected by using geometric constraints provided by the marker. Unlike most of the conventional techniques, the proposed method offers a framework for simultaneous acquisition of height and position of an individual resident in the image. The accuracy and the robustness of our technique is verified on the experimental results of several real video sequences from outdoor environments.

• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.1 s.20
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• pp.1-7
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• 2004

RADARSAT is one of many possible data sources that can play an important role in marine surveillance including ship detection because radar sensors have the two primary advantages: all-weather and day or night imaging. However, atmospheric effects on SAR imaging can not be bypassed and any remote sensing image has various geometric distortions, In this study, radiometric and geometric calibrations for RADARSAT/SAT data are tried using SGX products georeferenced as level 1. Even comparison of the near vs. far range sections of the same images requires such calibration Radiometric calibration is performed by compensating for effects of local illuminated area and incidence angle on the local backscatter, Conversion method of the pixel DNs to beta nought and sigma nought is also investigated. Finally, automatic geometric calibration based on the 4 pixels from the header file is compared to a marine chart. The errors for latitude and longitude directions are 300m and 260m, respectively. It can be concluded that the error extent is acceptable for an application to open sea and can be calibrated using a ground control point.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5006-5022
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• 2017

Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.