• Korean Journal of Radiology
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• v.2 no.4
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• pp.183-191
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• 2001

Objective: To document the signal characteristics of intracerebral hemorrhage (ICH) at evolving stages on diffusion-weighted images (DWI) by comparison with conventional MR images. Materials and Methods: In our retrospective study, 38 patients with ICH underwent a set of imaging sequences that included DWI, T1-and T2-weighted imaging, and fluid-attenuated inversion recovery (FLAIR). In 33 and 10 patients, respectively, conventional and echo-planar T2^* gradient-echo images were also obtained. According to the time interval between symptom onset and initial MRI, five stages were categorized: hyperacute (n=6); acute (n=7); early subacute (n=7); late subacute (n=10); and chronic (n=8). We investigated the signal intensity and apparent diffusion coefficient (ADC) of ICH and compared the signal intensities of hematomas at DWI and on conventional MR images. Results: DWI showed that hematomas were hyperintense at the hyperacute and late subacute stages, and hypointense at the acute, early subacute and chronic stages. Invariably, focal hypointensity was observed within a hyperacute hematoma. At the hyperacute, acute and early subacute stages, hyperintense rims that corresponded with edema surrounding the hematoma were present. The mean ADC ratio was 0.73 at the hyperacute stage, 0.72 at the acute stage, 0.70 at the early subacute stage, 0.72 at the late subacute stage, and 2.56 at the chronic stage. Conclusion: DWI showed that the signal intensity of an ICH may be related to both its ADC value and the magnetic susceptibility effect. In patients with acute stroke, an understanding of the characteristic features of ICH seen at DWI can be helpful in both the characterization of intracranial hemorrhagic lesions and the differentiation of hemorrhage from ischemia.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.402-412
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• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.4
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• pp.377-385
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• 2002

Ultrasonic tests employing non-ionizing radiation are preferred in nondestructive examinations since they are safe and simple in use. The same principles of the techniques have been taken as valuable tools in medical area for the diagnoses of diseases, in other words, defects of the human body. The paper overviews the principles of the medical diagnosis based on nondestructive ultrasonic tests, and then evaluates experimentally the clinical potential of C scan images not popular in medicine, for detecting the micro fractures of the cortical bone. In the experiment the micro bone fractures were created on the femurs of porks by loading three point bending forces (2-4kN) with the speed of 1 mm/min. As the extent of the fracture was altered, not only X ray images but also ultrasonic C scan images using a focused ultrasonic probe resonated at 25 MHz were obtained. The results showed that ultrasonic C scan images were capable of detecting the micro bone fractures which were not possible to identify by conventional X ray images.

• Journal of radiological science and technology
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• v.45 no.3
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• pp.255-262
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• 2022

In this study, by analyzing the examination time for each procedure, the appropriate workload of radiologic technologist is analyzed based on the actual examination time in the current clinical setting by comparing with the examination time in the radiology field setting of the health insurance review and assessment service. In addition, this result is introduced into the calculation of relate value units; it was attempted to provide accurate and objective evidence in the field of radiology. From May 2020 to December 2021, the study retrospectively investigated the examination times recorded in the electronic medical record and picture archiving and communication system at 5 tertiary general hospitals and 1 general hospital. The total of 16 examination parts are applied in this study, including the head, sinuses, chest, ribs, abdomen, pelvis, cervical, thoracic, lumbar, shoulder, elbow, wrist, hip, femur, knee, and ankle. The minimum number of images that could be obtained per radiation generator was 3.6 images for one hour, and the maximum was 6.4 images. When 50% median of procedure time is calculated, the minimum number of images that could be obtained was 16.7 images and maximum was 35.3 images; in addition, minimum examination time is 1.7 minutes, and maximum time is 3.6 minutes. In conclusion, it is judged that there will be insufficient explanation time for basic infection instructions such as hand hygiene during the examinations in current clinical practice. It is believed that radiologic technologists will contribute to providing higher-quality of radiation examination services to the public by complying with guidelines for work and setting appropriate workload on their own.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1309-1315
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• 2005

It is hard to protect the copyright of the medical images by the Copyright Act because the medical images have the digital property. Especially, if people copy the medical image, another original one will be created. Thus, people send the original medical image to the others unconsciously. After all, it can not dispute about who made the image for the first time. Nowadays, the medical environment has been changed to the digital environment rapidly. So, the study on the security of the medical image is needed. In this paper, we search the significant problems of the part and we research the security of the medical image using the watermark for addressing the problems. However, we could know that our study has the limitation of the legal certification because we could not guarantee about the integrity that is the important feature of the medical images.

• Clinical Endoscopy
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• v.51 no.6
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• pp.513-526
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• 2018

White light imaging (WLI) may not reveal early upper gastrointestinal cancers. Linked color imaging (LCI) produces bright images in the distant view and is performed for the same screening indications as WLI. LCI and blue laser imaging (BLI) provide excellent visibility of gastric cancers in high color contrast with respect to the surrounding tissue. The characteristic purple and green color of metaplasias on LCI and BLI, respectively, serve to increase the contrast while visualizing gastric cancers regardless of a history of Helicobacter pylori eradication. LCI facilitates color-based recognition of early gastric cancers of all morphological types, including flat lesions or those in an H. pylori-negative normal background mucosa as well as the diagnosis of inflamed mucosae including erosions. LCI reveals changes in mucosal color before the appearance of morphological changes in various gastric lesions. BLI is superior to LCI in the detection of early esophageal cancers and abnormal findings of microstructure and microvasculature in close-up views of upper gastrointestinal cancers. Excellent images can also be obtained with transnasal endoscopy. Using a combination of these modalities allows one to obtain images useful for establishing a diagnosis. It is important to observe esophageal cancers (brown) using BLI and gastric cancers (orange) surrounded by intestinal metaplasia (purple) and duodenal cancers (orange) by LCI.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.690-696
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• 2010

Web-based virtual collaboration is increasingly gaining popularity in almost every area in our society due to the fact that it can bridge the gap imposed by time and geographical constraints. However, in medical field, such collaboration has been less popular than other fields. Some of the reasons were timeliness, security, and preciseness of the information they are dealing with. In this paper, we are proposing a web-based distributed medical collaboration system called Virtual Collaboration System for Medicine (VCSM) for medical doctors that meet the needs. The proposed system consists of two parts - multimedia presentation and recordable virtual collaboration. The former supports synchronized multimedia presentation using Synchronous Multimedia Integration Language (SMIL.) It allows synchronization of the contents of a PowerPoint presentation file and a video file. The presentation may be provided to the participants before the discussion begins. Next, in the virtual collaboration stage, participants can use text along with associated symbols during the discussion over the presented medical images. The symbols such as arrows or polygons can be set or removed dynamically to represent areas of interest in digital images using so called layered architecture that separates image layer from annotation layer. XML files are used to record participants' opinions along with the symbols over some particular images

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.206-209
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• 1997

The stereostatic surgery becomes a important part of neurosurgery. The conventional style of stereostatic system uses a input method of film digitizing. It is time consuming and laborious. In this paper, we presented a system that can manage digital images from medical imaging machine to surgery assisting program. CT images were transferred in DICOM format to a surgery assisting computer in a operation room through PACS. The streotatic surgery assisting program processed the digital images and calculated the parameters that were required in steostatic surgery. The assisting program were developed that can detect the reference points automatically, transform CT coordinate to frame coordinate and calculate the RM (Riechert-Mundinger) frame. This system were applied to clinical cases in Seoul National Univ. Hospital. The two advantages of this system were revealed. The processing time from imaging to surgery parameters were much aster than conventional system. The surgery accuracy were more mininute as the digitizing error were reduced. This system were a good application of connecting imaging machines to clinical treatment system through PACS.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.116-124
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• 2021

It is important to differentiate between the target tissue (or organ) and the rest of the tissue before incision during surgery. And when it is necessary to preserve the differentiated tissues, the blood vessels connected to the tissue must be preserved together. Various non-invasive medical imaging methods have been developed for this purpose. We aimed to develop a medical imaging system that can simultaneously apply fluorescence imaging using indocyanine green (ICG) and laser speckle contrast imaging (LSCI) using laser speckle patterns. We designed to collect images directed to the two cameras on a co-axial optical path and to compensate equal optical path length for two optical designs. The light source used for fluorescence and LSCI the same 785 nm wavelength. This system outputs real-time images and is designed to intuitively distinguish target tissues or blood vessels. This system outputs LSCI images up to 37 fps through parallel processing. Fluorescence for ICG and blood flow in animal models were observed throughout the experiment.