• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.6
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• pp.103-110
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• 2016

The recent frequent cases of damage due to leakage of medical data and the privacy of medical patients is increasing day by day. The government says the Privacy Rule regulations established for these victims, such as prevention. Medical data guidelines can be seen 'national medical privacy guidelines' is only released. When replacing the image data between the institutions it has been included in the image file (JPG, JPEG, TIFF) there is exchange of data in common formats such as being made when the file is leaked to an external file there is a risk that the exposure key identification information of the patient. This medial image file has no protection such as encryption, This this paper, introduces a masking technique using a mosaic technique encrypting the image file contains the application to optical character recognition techniques. We propose pseudonymization technique of personal information in the image data.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.75-82
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• 2022

Medical data is one of the data that must be kept in safe containers, far from intrusion, viewing and modification. With the technological developments in hospital systems and the use of cloud computing, it has become necessary to save, encrypt and even hide data from the eyes of attackers. Medical data includes medical images, whether they are x-ray images of patients or others, or even documents that have been saved in the image format. In this review, we review the latest research and the latest tools and algorithms that are used to protect, encrypt and hide these images, and discuss the most important challenges facing these areas.

• Korean Journal of Digital Imaging in Medicine
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• v.16 no.1
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• pp.35-42
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• 2014

Heart related special images are classified as Cardiac US, XA, CT, MRI. Several Problem is caused by image compression, control and medical support point, so most big hospitals have created a Cadiac PACS differentially in past years. For this reason, create a conflict in inner colleague and patient, protector that result from 2 data processing server operating independently in 1 medical center area. For this reason, we sugges an alternative model of best medical control process together with understand the current situation on medical facility.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.92-95
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• 1994

As computer systems to make medical practice easy are widely used, a special hardware system processing medical data fast becomes more important. To meet the urgent demand for high speed image processing, especially image compression and decompression, we designed and implemented the medical image CODEC (COder/BECoder) based on MISD(Multiple Instruction Single Data stream) architecture to adopt parallelism in it. Considering not being a standart scheme of medical mage compression/decompress ion, the CODEC is designed programable and general. In this paper, we use JPEG (Joint Photographic Experts Group) algorithm to process images fast and evalutate it.

• The Korean Journal of Emergency Medical Services
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• v.18 no.3
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• pp.63-75
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• 2014

Purpose: The purpose of this study was to investigate the image about emergency medical technology (EMT) jobs and to identify factors influencing the image of EMT jobs among students of this department. Methods: A self-reported questionnaire was administered to 532 paramedic students in the cities of D, G, and J between May 28 and June 19, 2013. Data were analyzed by using the SPSS version 21.0 program. Results: The image about EMT jobs was positively related to self-esteem. However, the image about EMT jobs was negatively related to grade and hospital practice experience. In the multiple regression analysis, the adjusted $R^2$ value was .220 (p < .001). Conclusion: The importance of enhancing the self-esteem of paramedic students should be emphasized. Further research on the image about EMT jobs in the hospital practice setting is needed.

• 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 the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.759-766
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• 2017

In this paper, we preserve the transparency of digital contents by compressing and storing the medical image for a certain period so as to be safe and robust against various attacks of medical images. The proposed algorithm generates an encrypted image authentication code that extracts the feature value of the original image and combines it with the user's information. in order to extract hidden data, the authentication code is first decrypts the encrypted medical image and extracts the hidden data using the spatial characteristics of image. The proposed algorithm guarantees integrity when comparing extracted authentication code and newly generated authentication code for image authentication after directly inserting it into content itself through watermarking. We have proved various security of attack of image data and proved that the certification rate is improved to 98.4%.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.27-34
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• 1997

3-D image modeling is in high demand for automated visual inspection and non-destructive testing. It also can be useful in biomedical research, medical therapy, surgery planning, and simulation of critical surgery (i.e. cranio-facial). Image processing and image analysis are used to enhance and classify medical volumetric data. Analyzing medical volumetric data is very difficult In this paper, we propose a new image modeling method based on tetrahedrization to improve the visualization of three-dimensional medical volumetric data. In this method, the trivariate piecewise linear interpolation is applied through the constructed tetrahedral domain. Also, visualization methods including iso-surface, color contouring, and slicing are discussed. This method can be useful to the correct and speedy analysis of medical volumetric data, because it doesn't have the ambiguity problem of Marching Cubes algorithm and achieves the data reduction. We expect to compensate the degradation of an accuracy by using an adaptive sub-division of tetrahedrization based on least squares fitting.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.2
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• pp.39-43
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• 2007

In angiography, the global standard agreements of DICOM is lossless. But it brings on overload and takes too much store space in DICOM sever. Because of all those things we transmit images which is classified in subjective way. But this cause data loss and would be lead doctors to make wrong reading. As a result of that we try to transmit continued image (raw data) to reduce those mistakes. We got angiography images from the equipment(Allura FD20-Philips). And compressed it in two different methods(lossless & lossy fair). and then transmitted them to PACS system. We compared the quality of QC phantom images that are compressed by different compress method and compared spatial resolution of each images after CD copy. Then compared each Image's data volume(lossless & lossy fair). We measured spatial resolution of each image. All of them had indicated 401p/mm. We measured spatial resolution of each image after CD copy. We got also same conclusion (401p/mm). The volume of continued image (raw data) was 127.8MB(360.5 sheets on average) compressed in lossless and 29.5MB(360.5 sheets) compressed in lossy fair. In case of classified image, it was 47.35MB(133.7 sheets) in lossless and 4.5MB(133.7 sheets) in lossy fair. In case of angiography the diagnosis is based on continued image(raw data). But we transmit classified image. Because transmitting continued image causes some problems in PACS system especially transmission and store field. We transmit classified image compressed in lossless But it is subjective and would be different depend on radiologist. therefore it would make doctors do wrong reading when patients transfer another hospital. So we suggest that transmit continued image(raw data) compressed in lossy fair. It reduces about 60% of data volume compared with classified image. And the image quality is same after CD copy.

• 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.