• Journal of Biomedical Engineering Research
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• v.9 no.2
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• pp.195-210
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• 1988

We build up distributed database of medical picture and design and realize H/W & S/W of special image workstation. We build up high speed image transmission system for distributed database and retrieval of various medical pictures in w ard through image transmission system and realize integrated image diagnosis. This system improves medical service by speedy diagnosis and enables more precise diagnosis by integrated image diagnosis through distributed database. In economical view this system curtails huge cost of film processing and transmission, which make medical expense cheaf, because it does not use film. We built up PACS in pediatric hospital of Seoul National University Hopital and tested the system with various medical pictures and showed that speedy integrated image diagnosis is possible.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.977-991
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• 2000

In this paper, a medical image processing system was designed and implemented for morphometric and functional analysis of a human brain. The system is composed of image registration, ROI(region of interest) analysis, functional analysis, image visualization, 3D medical image database management system(DBMS), and database. The software processes an anatomical and functional image as input data, and provides visual and quantitative results. Input data and intermediate or final output data are stored to the database as several data types by the DBMS for other further image processing. In the experiment, the ROI analysis, for a normal, a tumor, a Parkinson's decease, and a depression case, showed that the system is useful for morphometric and functional analysis of a human brain.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.38-43
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• 2004

We designed and implemented a medical image query system, including a relational database and DBMS (database management system), which can visualize image data and can achieve spatial, attribute, and mixed queries. Image data used in querying can be visualized in slice, MPR(multi-planner reformat), volume rendering, and overlapping on the query system. To reduce spatial cost and processing time in the system. brain images are spatially clustered, by an adaptive Hilbert curve filling, encoded, and stored to its database without loss for spatial query. Because the query is often applied to small image regions of interest(ROI's), the technique provides higher compression rate and less processing time in the cases.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.197-202
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• 2016

This paper suggested that medical image database construction technique that generated and recognized from variable medical device and professional medical experts for the formalization and pattern extraction from informal medical images. And then we transformed informal image characteristics to digital data, and generated the meaningful pattern matching informations. Through this experienced works, so many related researchers can easily access the medical images database and use this formalized image informations on the variable fields.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.8-15
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• 2002

This Paper proposes designing and implementing the database system storing the medical images. This system collects the medical image when doctors operate and diagnose the patients using the endoscope in the orthopedics, then stores the medical image data to database. Therefore. system avoids duplicated medical data, retrieves and updates the medical data effectively. The medical image data can be shared to the multiple users and application programs. This system consists of the five components. that is, the input module acquiring the medical image from the endoscope. the modulo storing the medical image. the database design and implementation storms the patient's disease history and the medical image data, user friendly interface design and implementation, and the simple data retrieval engine. The features of the system are followed. The image catcher program using DirectShow is portable any image catcher board And because the image catcher algorithm is implemented as a public module, The throughput can be increased during the development of video and audio contents on internet.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.121-128
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• 1994

In this paper, MIlS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemnted system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression! decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

• Imaging Science in Dentistry
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• v.32 no.3
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• pp.129-134
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• 2002

Purpose : To implement the database system of oral and maxillofacial radiological images using a commercial medical image management software with personally developed classification code. Materials and methods : The image database was built using a slightly modified commercial medical image management software, Dr. Image v.2.1 (Bit Computer Co., Korea). The function of wild card '*' was added to the search function of this program. Diagnosis classification codes were written as the number at the first three digits, and radiographic technique classification codes as the alphabet right after the diagnosis code. 449 radiological films of 218 cases from January, 2000 to December, 2000, which had been specially stored for the demonstration and education at Dept. of OMF Radiology of Dankook University Dental Hospital, were scanned with each patient information. Results: Cases could be efficiently accessed and analyzed by using the classification code. Search and statistics results were easily obtained according to sex, age, disease diagnosis and radiographic technique. Conclusion : Efficient image management was possible with this image database system. Application of this system to other departments or personal image management can be made possible by utilizing the appropriate classification code system.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.2
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• pp.5-9
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• 2007

As developing the medical treatment image portion with the change of these times, PACS, which is able to digitalize image portion data, has a lot of data-based image data. Applying this PACS, we would like to settle down RNSXI(real-name shooting X -ray of inspector) system. We interviewed with P ACS's operators of university hospitals which is using PACS in Seoul about the present conditions whether using of RNSXI or not. And we inquired the RNSXI equipments, applying PACS database, and Interface conditions undertook to do in our hospital. All university hospitals in Seoul are set up the P ACS system. But no hospital use the RNSXI. In our hospital, we can check inspector' name or initials who exposure x-ray with the PACS Viewer by looking over equipments(CR, DR, US, MG, MR, CT) and Interface of the DICOM Header data. However, some equipments like RF and Angio can not check inspector' name or initials. Under the Film/System environment, RNSXI system has been used frequently like that inspector's signature or initial added to a patient data. Though the digital medical treatment was developed, RNSXI system was declined. It is necessary to using RNSXI system in order to improving radiologists' rights, even if it is not under the application of the medical treatment image laws. If RNSXI system use, radiologists should specialize in their major and the Repeat rate should be reduced. In environment of PACS, RNSXI system can be used by linking both the equipments and the Interface with a production enterprise of P ACS. Therefore RNSXI system applying the P ACS datebase should settle down in our medical system for being provided lots of data.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.131-134
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• 1988

In this paper, MIIS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemented system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression/decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

• Journal of Internet of Things and Convergence
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• v.2 no.4
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• pp.15-20
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• 2016

This paper describes the construction of knowledge data retrieval management system based on medical image CT. The developed system is aimed to improve the efficiency of the hospital by reading the medical images using the intelligent retrieval technology and diagnosing the patient 's disease name. In this study, the medical image DICOM file of PACS is read, the image is processed, and feature values are extracted and stored in the database. We have implemented a system that retrieves similarity by comparing new CT images required for medical treatment with the feature values of other CTs stored in the database. After converting 100 CT dicom provided for academic research into JPEG files, Code Book Library was constructed using SIFT, CS-LBP and K-Mean Clustering algorithms. Through the database optimization, the similarity of the new CT image to the existing data is searched and the result is confirmed, so that it can be utilized for the diagnosis and diagnosis of the patient.