• Journal of Broadcast Engineering
• /
• v.5 no.1
• /
• pp.94-101
• /
• 2000

User adaptive reception of broadcast programs includes the functionality such as the user adaptive filtering and browsing functionality. The user adaptive filtering means that the user can limit the list of programs to include only his/her favorite programs among hundreds of available programs. The user adaptive browsing means that the user can view a short summary of his/her selection in the way that he/she prefers. When the receiving system include the random access storage device, the automatic recording functionality of users favorite programs can be included. The user adaptive reception requires support from various meta-data such as user preference data and content description data. TV Anytime forum is a standardization effort to enable user adaptive TV reception, which means that the user can watch what s/he wants when s/he want in the way s/he wants. MPEG-7 includes not only the content description for broadcast applications but also other content descriptions such as structure information. This paper addresses the relationship between MPEG-7 and TV Anytime and investigates how MPEG-7 should be designed and be used to satisfy the requirements of the user adaptive reception of broadcast program.

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

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