• Journal of the Korean Society of Radiology
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• v.85 no.1
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• pp.147-160
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• 2024

Purpose To define an MRI scoring system for differentiating xanthogranulomatous cholecystitis (XGC) from wall-thickening type gallbladder cancer (GBC) and compare the diagnostic performance of the scoring system with the visual assessment of radiologists. Materials and Methods We retrospectively analyzed 23 and 35 patients who underwent abdominal MRI and were pathologically diagnosed with XGC and wall-thickening-type GBC after surgery, respectively. Three radiologists reviewed all MRI findings. We defined a scoring system using these MRI findings for differentiating XGC from wall-thickening type GBC and compared the area under the curve (AUC) of the scoring system with the visual assessment of radiologists. Results Nine MRI findings showed significant differences in differentiating the two diseases: diffuse gallbladder wall thickening (p < 0.001), mucosal uniformity (p = 0.002), intramural T2-high signal intensity (p < 0.001), mucosal retraction (p = 0.016), gallbladder stones (p < 0.001), T1-intermediate to high-signal intensity (p = 0.033), diffusion restriction (p = 0.005), enhancement pattern (p < 0.001), and phase of peak enhancement (p = 0.008). The MRI scoring system showed excellent diagnostic performance with an AUC of 0.972, which was significantly higher than the visual assessment of the reviewers. Conclusion The MRI scoring system showed better diagnostic performance than the visual assessment of radiologists to differentiate XGC from wall-thickening-type GBC.

• Korean Journal of Radiology
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• v.21 no.5
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• pp.625-626
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• 2020

• Korean Journal of Radiology
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• v.24 no.12
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• pp.1173-1175
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• 2023

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1272-1277
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• 2017

To assist radiologists for the characterization of breast masses, Computer-aided Diagnosis(CADx) system has been studied. The CADx system can improve the diagnostic accuracy of radiologists by providing objective information about breast masses. Morphological and texture features were extracted from the breast ultrasound images. Based on extracted features, the CADx system retrieves masses that are similar to a query mass from a reference library using a k-nearest neighbor (k-NN) approach. Eight similarity measures of distance, Euclidean, Chebyshev(Minkowski family), Canberra, Lorentzian($F_2$ family), Wave Hedges, Motyka(Intersection family), and Cosine, Dice(Inner Product family) are evaluated by ROC(Receiver Operating Characteristic) analysis. The Inner Product family measure used with the k-NN classifier provided slightly higher performance for classification of malignant and benign masses than those with the Minkowski, $F_2$, and Intersection family measures.

• Imaging Science in Dentistry
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• v.43 no.1
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• pp.17-23
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• 2013

Purpose: The purpose of this study was to assess cone-beam computed (CBCT) sialography imaging in the detection of different changes associated with lesions of salivary glands. Materials and Methods: This study consisted of 8 cases with signs and symptoms from salivary gland lesions. Conventional sialography using digital panoramic and lateral oblique radiographs and CBCT sialography were performed for each subject. The radiographs were evaluated by 3 radiologists independently of each other. The results were compared between conventional sialography and CBCT sialography in the evaluation of various lesions associated with the salivary glands. Results: There was an agreement between the radiologists in interpreting the lesions that affected salivary glands with both techniques. The detection of the presence of stones or filling defects, stenosis, ductal evagination, dilatation, and space occupying lesions was 83% for conventional sialography compared with CBCT sialography. CBCT sialography was superior to conventional sialography in revealing stones, stenosis, and strictures, especially in the second and third order branches. Conclusion: It would be advisable to perform CBCT sialography in cases of obstructive salivary gland diseases for better demonstration of the ductal system of the gland.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.1-8
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• 2009

Breast MRI is a cutting-edge technology in the diagnosis and intervention of breast abnormalities. Over the last decade, breast MRI has evolved from a research field to a clinical field. Radiologists should understand the indications, how to obtain adequate images, and how to interpret and report their findings. Breast MRI is now used in the differentiation of benign from malignant mass, preoperative staging of breast cancer patients, assessment of tumor response to neoadjuvant chemotherapy, and evaluation of women with breast implants. It can also be used as a supplemental screening modality for high-risk women. Qualified radiologists and adequate MRI technique are crucial for the success of these purposes. This review is focused on the indication, standardized use of lexicon and categorization of breast MRI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.678-700
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• 2023

Diagnosing breast diseases using ultrasound (US) images remains challenging because it is time-consuming and requires expert radiologist knowledge. As a result, the diagnostic performance is significantly biased. To assist radiologists in this process, computer-aided diagnosis (CAD) systems have been developed and used in practice. This type of system is used not only to assist radiologists in examining breast ultrasound images (BUS) but also to ensure the effectiveness of the diagnostic process. In this study, we propose a new approach for breast lesion localization and segmentation using a multi-scale pyramid of the ultrasound image of a breast organ and a convolutional semantic segmentation network. Unlike previous studies that used only a deep detection/segmentation neural network on a single breast ultrasound image, we propose to use multiple images generated from an input image at different scales for the localization and segmentation process. By combining the localization/segmentation results obtained from the input image at different scales, the system performance was enhanced compared with that of the previous studies. The experimental results with two public datasets confirmed the effectiveness of the proposed approach by producing superior localization/segmentation results compared with those obtained in previous studies.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.1
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• pp.11-22
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• 2023

Bone densitometry is a disease in which bones are easily broken due to metabolic bone disease, and DXA is used as a clinical standard test. Although DXA is a good method with good accuracy and reproducibility, it is frequently subject to test errors in testing and result analysis and analysis. Therefore, it is important to recognize the error issues that radiologists should basically be aware of when performing bone density tests, prevent erroneous diagnoses and treatments resulting from the results, and reduce the unnecessary costs associated with them. aim. The inspection must be carried out if the quality control of the equipment is basically continuously performed well before the inspection. Before starting the examination, the patient's age, sex, race, weight, pregnancy status, and any foreign objects that can be removed should be checked, and the examination should be performed in the correct posture. In addition, it is important to analyze results consistently. Radiologists, who play the most important role in ensuring accurate examinations, need to be aware of the potential for errors in advance and develop the ability to deal with the potential for errors in each examination. For that reason, regular education is considered essential.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.838-850
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• 2021

The incidence and prevalence of nontuberculous mycobacterial pulmonary disease (NTM-PD) is increasing worldwide, including in Korea, and the clinical importance of NTM-PD is also rapidly increasing. The diagnosis and management of NTM-PD is difficult. Radiologic evidence is mandatory to diagnose NTM-PD, and the radiologic findings may be the first evidence of the disease in many patients. Traditionally, NTM-PD demonstrates two different radiologic forms: fibrocavitary and nodular bronchiectatic. However, the disease also shows non-specific and a wide spectrum of radiologic features. Radiologists must be aware of the radiologic features of NTM-PD and should include them in the differential diagnosis. This review focuses on the epidemiology in Korea, diagnostic criteria, and radiological features of NTM-PD for radiologists.

• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.386-396
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• 2020

Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.