• Journal of the Korean Society of Radiology
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• v.6 no.2
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• pp.143-149
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• 2012

Today each hospital is trend that change rapidly by up to date, digitization and introducing newest medical treatment equipment. So, we introduce new CR system and supplement film system's shortcoming and PACS, EMR, RTP system's network that is using in hospital harmoniously and accomplish quality improvement of medical treatment and service elevation about business efficiency enlargement and patient Accordingly, we wish to introduce our case that integrate reflex that happen with radiation oncology here upon to PACS using CR system and estimate the availability. We measured that is Gantry, Collimator Star Shot, Light vs. Radiation, HDR QA(Dwell position accuracy) with Medical LINAC(MEVATRON-MX) Then, PACS was implemented on the digital images on the monitor that can be confirmed through the QA. Also, for cooperation with OCS system that is using from present source and impose code that need in treatment in each treatment, did so that Order that connect to network, input to CR may appear, did so that can solve support data mistake (active Pinacle's case supports DICOM3 file from present source but PACS does not support DICOM3 files.) of Pinacle and PACS that is Planning System and look at Planning premier in PACS. All image and data constructed integration to PACS as can refer and conduct premier in Hospital anywhere using CR system. Use Dosimetry IP in Filmless environment and QA's trial such as Light/Radition field size correspondence, gantry rotation axis' accuracy, collimator rotation axis' accuracy, brachy therapy's Dwell position check is available. Business efficiency by decrease and so on of unnecessary human strength consumption was augmented accordingly with session shortening as that integrate premier that is neted with radiation oncology using CR system to PACS. and for the future patient information security is essential.

• Progress in Medical Physics
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• v.10 no.2
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• pp.73-81
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• 1999

Scatter correction for single photon emission computed tomography (SPECT) plays an important role to improve image quality and quantitation. The purpose of this study was to investigate three scatter correction methods using Monte Carlo simulation. Point source and Jaszack phantom filled with Tc-99m were simulated by Monte Carlo code, SIMIND. For scatter correction, we applied three methods, Compton window (CW) method, triple window (TW) method, and dual photopeak window (DPW) method. Point sources located at various depths along the center line within a 20-cm phantom were simulated to calculate the window ratios and corresponding scatter fractions by evaluating the polynomial coefficients for DPW method. Energy windows were located in W$_1$=92-125 keV, W$_2$=124-126 keV, W$_3$=136-140 keV, W$_4$=140-141 keV, and W$_{5}$=154-156 keV. The results showed that in Jaszack phantom with cold sphere and hot sphere, the TW gave the closest contrast and percentage recovery to the ideal image, respectively, while CW overestimated and DPW underestimated the contrast of ideal one. All three scatter correction methods showed an improved image contrast. In conclusion, scatter correction is essential for improving image contrast and accurate quantification. The choice of scatter correction method should be made on the basis of accuracies and ease of implementation.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.19-27
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• 2010

An region of interest processing technique is to handle preferentially some part of an image dynamically according to region of interest of the users in JPEG2000 image. A small image is not important, but in a big image the specified region that the user indicated has to be handled preferentially because it takes long time to display the whole image. If the user indicates a region of the outline image, the browser masks the region and sends the mask information to the source that transmitted the image. The server which got the mask information preferentially sends the code blocks matching the masks. Here, quickly generating mask information is important, so, in this paper using predefined 48 mask patterns, selecting one of the patterns according to the distribution of ROI(Region-of-Interest) and background, we remarkably reduced the time computing the mask region. Blocks that the patterns are applied are the blocks mixed of ROI and background in a block. If a whole block is an ROI or a background, these patterns are not applied. As results, comparing to the method that precisely handles ROI and background, the quality is unsatisfactory but the processing time remarkably reduced.