• Journal of the Korean Society for Precision Engineering
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• v.25 no.1
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• pp.22-34
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• 2008

• Journal of Digital Convergence
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• v.12 no.10
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• pp.329-335
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• 2014

With the spread of mobile phones and wireless networks, medical imaging needs to be accessible outside the hospital for patients. We develop the mobile PACS platform that allows doctors or patients to store, search, query and transfer medical images for their convenience. This system is a mobile based platform that patients DICOM images can be viewed from the hospital PACS server, then they can be converted according to smart standardization. For this, we designed the platform to transfer the data between PACS, mPACS and users. Also we suggest to use DICOM transformation processing to display DICOM images in PACS server.

• Korean Journal of Digital Imaging in Medicine
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• v.7 no.1
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• pp.23-31
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• 2005

원격진료 홈네트워크 아파트 진료용 키오스크 모바일주치의 등으로 대표되는 U-헬스케어에 있어서 기초가 되는 것은 의료정보를 디지털화해서 전자적 자료의 형태로 저장 보관하고 이를 송 수신할 수 있는 기술이라고 할 수 있다. 우리나라의 경우, U-Korea 전략의 하나로 보건복지부가 주축이 되어 2005년 10월 현재 국가보건의료정보화계획(ISP)을 수립하기 위한 작업을 추진중에 있다. 여기서, 예컨대 임상병리검사소견이나 방사선촬영소견 등의 의료정보가 전자적 장치에 의해 디지털화 할 경우 디지털 의료정보가 되는 것이며, 이 가운데 특히 방사선촬영소견 등 방사선분야의 모든 촬영기록이 PACS시스템을 통해 기재되거나 저장 전송될 경우 이를 디지털 의료영상정보라고 할 수 있다. 그런데 오늘날 정보통신기술의 발달로 말미암아 디지털 의료영상정보를 포함한 디지털의료정보는 대량적으로 수집 저장되고 유통 내지 공동활용이 보편화되어 감에 따라 그 의료정보의 보호에 관한 문제가 중요한 이슈로 대두되고 있다. 결론적으로 말하자면, 이러한 디지털 의료영상정보가 전자의무기록(EMR) 형태로 저장 보관되는 경우 이는 전자의무기록에 관한 법률규정이 적용되어 법률적 보호를 받게 되며, 그 보호의 강도는 종래 오프라인 상의 의료정보 보호보다 한층 강화된 규정을 두고 있다. 이와 같은 흐름에 있어서 최근 정부가 국가보건의료정보화계획 수립과 함께 제정작업을 추진하고 있는 가칭 의료정보화촉진 및 개인정보보호에 관한 법률(안)은 시사점이 크다고 보기 때문에 소개하고자 한다.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.81-81
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• 2003

목적 : 현재, 많은 병원이 방사선과 의료영상정보를 기존의 필름형태로 판독하고, 진료하는 방식에서 PACS 를 도입하여 디지털 형태로 영상을 전송, 저장, 검색, 판독하는 환경으로 변화하고 있다. 한편, PACS 가 가지는 가장 큰 제한점은 휴대성의 결핍이다. 본 연구는 이동형 장치가 가지는 호스트의 이동성 및 휴대성의 장점들을 살리면서, 무선 채널 용량의 한계, 무선 링크 사용이라는 제약점들을 감안하여 의료영상을 JPEG2000 영상압축 방식으로 부호화한 후 무선 환경을 고려한 전송 패킷의 크기를 결정하고자 하였으며, 무선 통신 중 발생되는 패킷 손실에 대응하기 위한 자동 오류 수정 기능도 함께 구현하고자하였다. 방법 : Window 2000 운영체계에서 의료영상을 로드하고, 데이터베이스화하며, 저장하고, 다른 네트워크와 접속, 제어가 가능한 PC급 서버를 구축하였다. 영상데이터는 무선망을 통해 전송하기 때문에 가장 높은 압축비율을 지원하면서 에너지 밀도가 높은 JPEG2000 알고리즘을 사용하여 영상을 압축하였다. 또한, 무선망 사용으로 인한 패킷 손실에 대비하여, 영상을 JPEG2000 방식으로 부호화한 후 각 블록단위로 전송하였다. 결과 : PDA에서 JPEG2000 영상을 복호화 하는데 걸리는 시간은 256$\times$256 크기의 MR 뇌영상의 경우 바로 확인할 수 있었지만, 800$\times$790 크기의 CR 흉부 영상의 경우 약 5 초 정도의 시간이 걸렸다. CDMA 1X(Code Division Multiple Access 1st Generation) 모듈을 사용하여 영상을 전송하는 경우, 256 byte/see 정도에서는 안정된 전송 결과를 보여주었고, 1 Kbyte/see 정도의 전송의 경우 중간 중간에 패킷이 손실되는 결과를 관찰할 수 있었다. 반면 무선 랜의 경우 이보다 더 큰 패킷을 전송하더라도 문제점은 발견되지 않았다. 결론 : 현재의 PACS는 유선과 무선사이의 인터페이스의 부재로 인해 유무선 연동이 되지 못하고 있다. 따라서 이동형 JPEG2000 영상 뷰어는 PACS가 가지는 문제점인 휴대성을 보완하기 위하여 개발되었다. 또한 무선망이 가지는 데이터 손실에 대하여서도 허용할 수 있는 범위에서 재전송을 가능하게 함으로서 약한 연결성을 보완하였다. 본 JPEG2000 영상 뷰어 시스템은 기존 유선상의 PACS와 이동형 장치간에 유기적인 인터페이스 역할을 하리라 기대된다.

• Korean Journal of Digital Imaging in Medicine
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• v.6 no.1
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• pp.9-18
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• 2003

디지털 영상 검출기와 디스플레이 기술의 발달과 의료영상전달시스템(PACS)의 출현은 전통적 필름방식에 비하여 디지털 방식으로 방사선과 영상을 획득하고 전송, 저장하는 매우 효과적인 수단을 제공하고 있다. 2002년 8월, 연세의료원 세브란스병원은 진단 영상 판독 목적으로 18 대의 CRT(Braco View, Belgium)와 32대의 평판 LCD(Totoku Electric Co., Ltd., Japan) 디스플레이 장치를 GE full-PACS(GE 메디칼시스템코리아 : GEMSK)와 연계하여 설치 완료하였다. 본 연구에서, 기하학적 왜곡, 반사, 휘도 반응, 휘도 균일도, 분해능, 노이즈,베일링 글레어, 칼라 균일도 항목들을 AAPM TG18 보고서 9.0에 따라서 시각적 그리고 부분적으로는 정량적인 방법으로 인수검사를 실시하여 보고한다. 사용된 장비는 색도계로도 사용되는 간편한 휘도계, TG18 테스트 패던, AAPM Tg18 AT plug-in software(Barco View Ltd., Kortrijk, Belgium)이었다. 칼라 균일도를 제외한 모든 테스트 결과는 AAPM TG18에서 권고하는 기준에 일치하였으며 진단 영상 판독에 사용하기에 전적으로 수락할 수 있는 성능이었다. 결론으로, 사용된 인수검사는 단지 인수 검사 표준을 제공하는 것 뿐만 아니라 품질검사(QC)의 지침, 판독 환경의 최적화 그리고 교체 시기나 업그레이드 시기를 결정하여주는 중요한 역할을 할 수 있을 것이다.

• Progress in Medical Physics
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• v.14 no.2
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• pp.124-130
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• 2003

Currently, as a consequence of PACS (Picture Archiving Communication System) implementation many hospitals are replacing conventional film-type interpretations of diagnostic medical images with new digital-format interpretations that can also be saved, and retrieve However, the big limitation in PACS is considered to be the lack of mobility. The purpose of this study is to determine the optimal communication packet size. This was done by considering the terms occurred in the wireless communication. After encoding medical image using JPGE2000 image compression method, This method embodied auto-error correction technique preventing the loss of packets occurred during wireless communication. A PC class server, with capabilities to load, collect data, save images, and connect with other network, was installed. Image data were compressed using JPEG2000 algorithm which supports the capability of high energy density and compression ratio, to communicate through a wireless network. Image data were also transmitted in block units coeded by JPEG2000 to prevent the loss of the packets in a wireless network. When JPGE2000 image data were decoded in a PUA (Personal Digital Assistant), it was instantaneous for a MR (Magnetic Resonance) head image of 256${\times}$256 pixels, while it took approximately 5 seconds to decode a CR (Computed Radiography) chest image of 800${\times}$790 pixels. In the transmission of the image data using a CDMA 1X module (Code-Division Multiple Access 1st Generation), 256 byte/sec was considered a stable transmission rate, but packets were lost in the intervals at the transmission rate of 1Kbyte/sec. However, even with a transmission rate above 1 Kbyte/sec, packets were not lost in wireless LAN. Current PACS are not compatible with wireless networks. because it does not have an interface between wired and wireless. Thus, the mobile JPEG2000 image viewing system was developed in order to complement mobility-a limitation in PACS. Moreover, the weak-connections of the wireless network was enhanced by re-transmitting image data within a limitations The results of this study are expected to play an interface role between the current wired-networks PACS and the mobile devices.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.245-252
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• 2020

The purpose of this study was intended to recognize the importance of quality control (QC) in order to reduce exposure and improve image quality by comparing the center-point (CP) of according to hospital grade and the difference between X-ray field (XF) and light field (LF) in diagnostic digital X-ray devices. XF and LF size, CP were measured in 12 digital X-ray devices at 10 hospitals located in 00 metropolitan cities. Phantom was made in different width respectively, using 0.8 mm wire after attaching to the standardized graph paper on transparent plastic plate and marked as cross wire in the center of the phantom. After placing the phantom on the table of the digital X-ray device, the images were obtained by shooting it vertically each field of survey. All images were acquired under the same conditions of exposure at distance of 100cm between the focus-detector. XF and LF size, CP error were measured using the picture archiving communication system. data were expressed as mean with standard error and then analyzed using SPSS ver. 22.0. The difference in field between the XF and LF size was the smallest in clinic, followed by university hospitals, hospitals and general hospitals. Based on the university hospitals with the least CP error, there was a statistically significant difference in CP error between university hospitals and clinics (p=0.024). Group less than 36-month after QC had fewer statistical errors than 36-month group (0.26 vs. 0.88, p=0.036). The difference between the XF and LF size was the lowest in clinic and CP error was the lowest in university hospital. Moreover, hospitals with short period of time after QC have fewer CP error and it means that introduction of timely QC according to the QC items is essential.

• Progress in Medical Physics
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• v.19 no.1
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• pp.63-72
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• 2008

With recent advancement of the medical imaging systems and picture archiving and communication system (PACS), installation of digital radiography has been accelerated over past few years. Moreover, Computed Radiography (CR) which was well established for the foundation of digital x-ray imaging systems at low cost was widely used for clinical applications. This study analyzes imaging characteristics for two systems with different pixel sizes through the Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE). In addition, influence of radiation dose to the imaging characteristics was also measured by quantitative assessment. A standard beam quality RQA5 based on an international electro-technical commission (IEC) standard was used to perform the x-ray imaging studies. For the results, the spatial resolution based on MTF at 10% for Agfa CR system with I.P size of $8{\times}10$ inches and $14{\times}17$ inches was measured as 3.9 cycles/mm and 2.8 cycles/mm, respectively. The spatial resolution based on MTF at 10% for Fuji CR system with I.P size of $8{\times}10$ inches and $14{\times}17$ inches was measured as 3.4 cycles/mm and 3.2 cycles/mm, respectively. There was difference in the spatial resolution for $14{\times}17$ inches, although radiation dose does not effect to the MTF. The NPS of the Agfa CR system shows similar results for different pixel size between $100{\mu}m$ for $8{\times}10$ inch I.P and $150{\mu}m$ for $14{\times}17$ inch I.P. For both systems, the results show better NPS for increased radiation dose due to increasing number of photons. DQE of the Agfa CR system for $8{\times}10$ inch I.P and $14{\times}17$ inch I.P resulted in 11% and 8.8% at 1.5 cycles/mm, respectively. Both systems show that the higher level of radiation dose would lead to the worse DQE efficiency. Measuring DQE for multiple factors of imaging characteristics plays very important role in determining efficiency of equipment and reducing radiation dose for the patients. In conclusion, the results of this study could be used as a baseline to optimize imaging systems and their imaging characteristics by measuring MTF, NPS, and DQE for different level of radiation dose.