Earticle

This study aim to investigate image characteristics due to focus-grid and head phantom decentering from the armorphos silicon thin film transistor detector the fixed focus-grid is applied, wish to propose right use method of digital medical equipment. Acquired image according to focus-grid and head phantom position decentering using head phantom on armorphos silicon thin film transistor detector the fixed focus-grid is applied, acquired image evaluate pixel value, histogram, plot profile, surface plot using NIH (Image J) image analysis program and compared decentering image with standai-d image. Mean value and standard deviation value of focus-grid lateral decentering and duplex decentering of focus-grid and head phantom decreased by ratio, consequently increase of horizontality, diagonal decentering, also, deteriorated contrast of image because frequency of high pixel value decreases fairly, according increases decentering, image distortion phenomenon was increase, by next time, pixel mean value of head phantom decentering was no big change but horizontality, diagonal, mean value and standard deviation value of pixel decreased by ratio. Even if increase pixel noise of image because wide latitude and post processing ability of digital detector, radiotechnologist can not recognize. Therefore, radiotechnologist must recognize correctly the photographing factors which increases pixel noise on the grid system installation digital detector and should exam.

This study applies in case of operating an exam using by the conti*ast order or inputting an order of a contrast media the exam of Radiology Department. It is developed for helping decision making as regards a process of an exam from reading the creatinine value automatically linked with Laboratory Information System It can be confirmed by real-time information; therefore, the creditability of the information is able to be improved. We will create the base for Patient Monitoring System with the data from the side effect of the creatinine value and allergies. Decision Support System minimize the inconvenience and the riskiness of the given contrast medium for CT tests. We would like to improve medical services by providing a standard circumstance where patients are able to run tests safely and comfortably.

Our objective was to evaluate the CT attenuation coefficient and noise of spatial domain filtering as an alternative to additional image reconstruction using different kernels in abdominal CT. Derived from thin collimated source images was generated using abdomen BIO (very smooth), B20 (smooth), B30 (medium smooth), B40 (medium), B50 (medium sharp), B60 (sharp), B70 (very sharp) and B80 (ultra sharp) kernels. Quantitative CT coefficient and noise measurements provided comparable HU (hounsfield) units in this respect. CT attenuation coefficient (mean HU) values in the abdominal were 60.4 〜 62.2 HU and noise (7.6 〜 63.8 HU) in the liver parenchyma. In the stomach a mean (CT attenuation coefficient) of -2.2 - 0.8 HU and noise (10.1 〜 82.4 HU) was measured. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. CT images increase the diagnostic accuracy may be controlled by adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undeigoing the examination.

1. Purpose This study is to present effective exposure conditions to acquire the best image of simple abdomen in Film Screen (F.S) system and Computed Radiography (C.R) system. 2. Method In the F.S system, while an exposure condition was fixed as 70kVp, images of a patients simple abdomen were taken under the different mAs exposure conditions. Among these images, the best one was chosen by radiologists and radiological technologists. In the C.R system, the best image of the same patient was acquired with the same method from the F.S system. Both characteristic curves from F.S system and C.R system were analyzed . 3. Results In the F.S system, the best exposure condition of simple abdomen was 70kVp and 20mAs. In the CR system, with the fixed condition at 70kVp, the image densities of human organs, such as liver, kidney, spleen, psoas muscle, lumbar spine body and iliac crest, were almost same despite different environments (3.2mAs, 8mAs, 12mAs, 16mAs and 20mAs). However, when the exposure conditions were over or under (below) 12mAs, the images between the abdominal wall and the directly exposed part became blurred because the gap of density was decreased. In the C.R system, while the volume of mAs was decreased, an artifact of quantum mottle was increased. 4. Conclusion This study shows that the exposure condition in the C.R system can be reduced 40% than in the F.S system. This paper concluded that when the exposure conditions are set in CR environment, after the analysis of equipment character, such as image processing system(EDR : Exposure Data Recognition processing), PACS and so on, the high quality of image with maximum information can be acquired with a minimum exposure dose .

PACS has been run at the Kyung Hee University Medical Center(KHMC) since 2001, and the installation and operation of PACS have contributed to automation and quantification of KHMC's medical environment. During these five years our greatest concern is how to make our own guiding principle of diagnostic monitor QA which is adapted to international standards. In accordance with the terms of 'KHMC QA Guideline', 'AAPM TG18', 'SMPTE RP133', 'DICOM Part14', 'DIN V 6868-57', 'JESRA X-0093', 'JIS Z4752-2-5' and 'KCARE', concern about quality assurance of medical images are on the increase. With the investigation of acceptance testing and quality control of international standards for medical display devices, and data collection and analysis for recommended guideline, it is reported that acceptance testing(quality control), including geometrical distortion, display reflection, luminance response, luminance uniformity, display resolution, display noise, veiling glare and color chromaticity being adequate and effective to domestic hospital environments for medical display devices and assessment methods according to each performance. Accordingly, KHMC classified the checkpoint items by period, at the time of monitor setting, monthly, quarterly, half-yearly and annually. Periodic classfication of checkpoint items for monitor QA makes a good guideline for image QA/QC and useful guideline for persistent good quality of monitor.