• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.35 no.2
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• pp.143-149
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• 2024

Objectives: This study aimed to identify the effectiveness of treatment programs for children with reading (RD) or mathematics disorders (MD). Structured treatment programs were developed to improve phonological awareness and number sense among children and adolescents with RD or MD, respectively, and the effectiveness of the learning disorder treatment programs were evaluated. Methods: We used standardized, objective diagnostic, and evaluation tools not only to recruit participants with RD, MD, or comorbid attention deficit and hyperactivity disorder, but also to assess the effectiveness of the treatments regarding both improved core neurocognitive deficits of RD or MD and academic achievement. Forty children with RD or MD received one-on-one treatments from therapists. Results: In the RD group, treatment effects were observed in all subtests. In the word and paragraph reading tests, the accuracy rates and fluency improved. The results of the phonological working memory test, word-sound correspondence test, and rapid automatic naming tests also improved. In the MD group, the accuracy rate and fluency on the arithmetic test improved. An increase in the accuracy rate in the size and distance comparison tests and a decrease in the error rate in the estimation test were also observed. However, there were no improvements in reaction time in these subtests. Conclusion: Learning disorder treatment programs that focus on improving phonological awareness or number sense in children with RD or MD improved achievement, phonological awareness, and number sense.

• Radiation Oncology Journal
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• v.22 no.1
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• pp.33-39
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• 2004

Purpose : A tumor registry system for the patients treated by radiotherapy at Samsung Medical Center since the opening of a hospital at 1994 was employed. In this study, the tumor registry system was introduced and the validity of the tumor registration was analyzed. Materials and Methods: The tumor registry system was composed of three parts: patient demographic, diagnostic, and treatment Information. All data were input in a screen using a mouse only. Among the 10,000 registered cases in the tumor registry system until Aug, 2002, 199 were randomly selected and their registration data were compared with the patients' medical records. Results : Total input errors were detected on 15 cases (7.5%). There were 8 error items In the part relating to diagnostic Information: tumor site 3, pathology 2, AJCC staging 2 and performance status 1. In the part relating to treatment information there were 9 mistaken items: combination treatment 4, the date of initial treatment 3 and radiation completeness 2. According to the assignment doctor, the error ratio was consequently variable. The doctors who 010 no double-checks showed higher errors than those that 010 (15.6%:3.7%). Conclusion: Our tumor registry had errors within 2% for each Item. Although the overall data qualify was high, further improvement might be achieved through promoting sincerity, continuing training, periodic validity tests and keeping double-checks. Also, some items associated with the hospital Information system will be input automatically In the next step.

• Journal of radiological science and technology
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• v.35 no.1
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• pp.1-7
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• 2012

Dual Energy X-ray Absorptiometry(DEXA) is commonly used to diagnose Osteoporosis. The errors of DEXA bone density operation are caused by operator, bone mineral density meter, blood testing, patient. We focus on operator error then study about how much influence operator's region of intest(ROI) in bone testing result. During from March to July in 2011. 50 patients ware selected respectively from 30, 40, 50, 60, and 70 age groups who came to Korea University Medical Center(KUMC) for their Osteoporosis treatment. A-test was performed with usually ROI and B-test was performed with most widely ROI. Then, We compare A-test and B-test for find maximum difference of T-score error which occurred operator ROI controlling. Standard deviation of T-score of B-test showed 0.1 higher then A-test in femur neck. Standard deviation of B-test showed 0.2 higher then A-test in Ward's area which in Greater trocanter and Inter trocanter. Standard deviation of B-test showed 0,1 lower then A-test in L-1. Bone density testing about Two hundred patients results are as follow. When operator ROI was changed wider than normal ROI, bone density of femur was measured more higher but bone density of L-spine was measured more lower then normal bone density. That means, sometime DEXA bone density testing result is dependent by operator ROI controlling. This is relevant with the patient's medicine and health insurance, thus, tester always keep the size of ROI for to prevent any problem in the patient.

• Journal of the Korean Society of Radiology
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• v.6 no.6
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• pp.455-464
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• 2012

This study suggested evaluation of approximately exposure to low-dose ionization radiation from medical images using a computed radiography (CR) system in standard X-ray examination and experimental model can compare diagnostic reference level (DRL) will suggest on optimization condition of guard about medical radiation of low dose space. Entrance surface dose (ESD) cross-measuring by standard dosimeter and optically stimulated luminescence dosimeters (OSLDs) in experiment condition about tube voltage and current of X-ray generator. Also, Hounsfield unit (HU) scale measured about each experiment condition in CR system and after character relationship table and graph tabulate about ESD and HU scale, approximately radiation dose about head, neck, thoracic, abdomen, and pelvis draw a measurement. In result measuring head, neck, thoracic, abdomen, and pelvis, average of ESD is 2.10, 2.01, 1.13, 2.97, and 1.95 mGy, respectively. HU scale is $3,276{\pm}3.72$, $3,217{\pm}2.93$, $2,768{\pm}3.13$, $3,782{\pm}5.19$, and $2,318{\pm}4.64$, respectively, in CR image. At this moment, using characteristic relationship table and graph, ESD measured approximately 2.16, 2.06, 1.19, 3.05, and 2.07 mGy, respectively. Average error of measuring value and ESD measured approximately smaller than 3%, this have credibility cover all the bases radiology area of measurement 5%. In its final analysis, this study suggest new experimental model approximately can assess radiation dose of patient in standard X-ray examination and can apply to CR examination, digital radiography and even film-cassette system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1082-1090
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• 2009

Peak expiratory flow rate(PEF) is a very important diagnostic parameter obtained from the forced vital capacity(FVC) test. The expiratory flow rate increases during the short initial time period and may cause measurement error in PEF particularly due to non-ideal dynamic characteristic of the transducer. The present study evaluated the initial rise slope($S_r$) on the flow rate signal to compensate the transducer output data. The 26 standard signals recommended by the American Thoracic Society(ATS) were generated and flown through the velocity-type respiratory air flow transducer with simultaneously acquiring the transducer output signal. Most PEF and the corresponding output($N_{PEF}$) were well fitted into a quadratic equation with a high enough correlation coefficient of 0.9997. But only two(ATS#2 and 26) signals resulted significant deviation of $N_{PEF}$ with relative errors>10%. The relationship between the relative error in $N_{PEF}$ and $S_r$ was found to be linear, based on which $N_{PEF}$ data were compensated. As a result, the 99% confidence interval of PEF error was turned out to be approximately 2.5%, which was less than a quarter of the upper limit of 10% recommended by ATS. Therefore, the present compensation technique was proved to be very accurate, complying the international standards of ATS, which would be useful to calibrate respiratory air flow transducers.

• Tuberculosis and Respiratory Diseases
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• v.62 no.6
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• pp.523-530
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• 2007

Background: A ThinPrep$^{(R)}$ Processor was developed to overcome the limitations of conventional cytology and is widely used to diagnose various cancers. This study compared the diagnostic efficacy of conventional cytology for lung cancer with that of the ThinPrep$^{(R)}$ cytology using the bronchial washing fluid. Methods: The bronchial washing fluid of 790 patients from Jan. 2002 to Dec. 2006, who were suspected of gaving a lung malignancy, was evaluated. Both ThinPrep$^{(R)}$ and conventional cytology were performed for all specimens. Result: Four hundred forty-six men and 344 women were enrolled in this study, and 197 of them were diagnosed with cancer from either a bronchoscopic biopsy or a percutaneous needle aspiration biopsy. ThinPrep$^{(R)}$ cytology showed a sensitivity, specificity, positive predictive value, negative predictive value and false negative error rate of 71.1%, 98.0%, 92.1%, 91.1%, 8.9%, respectively. The conventional cytology showed sensitivity, specificity, positive predictive value, nagative predictive value and false negative error rate of 57.9%, 98.0%, 90.5%, 87.5%, 12.5%, respectively. For central lesions, the sensitivity of conventional cytology and ThinPrep$^{(R)}$ were 70.1% and 82.8%, respectively. Conclusion: ThinPrep$^{(R)}$ cytology showed a higher sensitivity and lower false negative error rate than conventional cytology. This result was unaffected by the histological classification of lung cancer. Therefore, ThinPrep$^{(R)}$ cytology appears to be a useful method for increasing the detection rate of lung cancer in bronchial washing cytology test.

• Radiation Oncology Journal
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• v.18 no.4
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• pp.345-354
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• 2000

Purpose : Conventional radiation therapy Portal images gives low contrast images. The purpose of this study was to enhance image contrast of a linacgram by developing a low-cost image processing method. Materials and Methods : Chest linacgram was obtained by irradiating humanoid Phantom and scanned using Diagnostic-Pro scanner for image processing. Several types of scan method were used in scanning. These include optical density scan, histogram equalized scan, linear histogram based scan, linear histogram independent scan, linear optical density scan, logarithmic scan, and power square root scan. The histogram distribution of the scanned images were plotted and the ranges of the gray scale were compared among various scan types. The scanned images were then transformed to the gray window by pallette fitting method and the contrast of the reprocessed portal images were evaluated for image improvement. Portal images of patients were also taken at various anatomic sites and the images were processed by Gray Scale Expansion (GSE) method. The patient images were analyzed to examine the feasibility of using the GSE technique in clinic. Results :The histogram distribution showed that minimum and maximum gray scale ranges of 3192 and 21940 were obtained when the image was scanned using logarithmic method and square root method, respectively. Out of 256 gray scale, only 7 to 30$\%$ of the steps were used. After expanding the gray scale to full range, contrast of the portal images were improved. Experiment peformed with patient image showed that improved identification of organs were achieved by GSE in portal images of knee joint, head and neck, lung, and pelvis. Conclusion :Phantom study demonstrated that the GSE technique improved image contrast of a linacgram. This indicates that the decrease in image quality resulting from the dual exposure, could be improved by expanding the gray scale. As a result, the improved technique will make it possible to compare the digitally reconstructed radiographs (DRR) and simulation image for evaluating the patient positioning error.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.31-39
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• 2009

Purpose : This study proposes the keyhole method in order to improve the time resolution of the proton resonance frequency(PRF) MR temperature monitoring technique. The values of Root Mean Square (RMS) error of measured temperature value and Signal-to-Noise Ratio(SNR) obtained from the keyhole and full phase encoded temperature images were compared. Materials and Methods : The PRF method combined with GRE sequence was used to get MR temperature images using a clinical 1.5T MR scanner. It was conducted on the tissue-mimic 2% agarose gel phantom and swine's hock tissue. A MR compatible coaxial slot antenna driven by microwave power generator at 2.45GHz was used to heat the object in the magnetic bore for 5 minutes followed by a sequential acquisition of MR raw data during 10 minutes of cooling period. The acquired raw data were transferred to PC after then the keyhole images were reconstructed by taking the central part of K-space data with 128, 64, 32 and 16 phase encoding lines while the remaining peripheral parts were taken from the 1st reference raw data. The RMS errors were compared with the 256 full encoded self-reference temperature image while the SNR values were compared with the zero filling images. Results : As phase encoding number at the center part on the keyhole temperature images decreased to 128, 64, 32 and 16, the RMS errors of the measured temperature increased to 0.538, 0.712, 0.768 and 0.845$^{\circ}C$, meanwhile SNR values were maintained as the phase encoding number of keyhole part is reduced. Conclusion : This study shows that the keyhole technique is successfully applied to temperature monitoring procedure to increases the temporal resolution by standardizing the matrix size, thus maintained the SNR values. In future, it is expected to implement the MR real time thermal imaging using keyhole method which is able to reduce the scan time with minimal thermal variations.

• Journal of Radiation Protection and Research
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• v.39 no.3
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• pp.150-158
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• 2014

Radiation-related practitioners and radiation-treated patients at medical institutions are inevitably exposed to radiation for diagnosis and treatment. Although standards for maximum doses are recommended by the International Commission on Radiological Protection (ICPR) and the International Atomic Energy Agency (IAEA), more direct and available measurement and analytical methods are necessary for optimal exposure management for potential exposure subjects such as practitioners and patients. Thus, in this study we developed a system for real-time radiation monitoring at a distance that works with existing portable device. The monitoring system comprises three parts for detection, imaging, and transmission. For miniaturization of the detection part, a scintillation detector was designed based on a silicon photomultiplier (SiPM). The imaging part uses a wireless charge-coupled device (CCD) camera module along with the detection part to transmit a radiation image and measured data through the transmission part using a Bluetooth-enabled portable device. To evaluate the performance of the developed system, diagnostic X-ray generators and sources of $^{137}Cs$, $^{22}Na$, $^{60}Co$, $^{204}Tl$, and $^{90}Sr$ were used. We checked the results for reactivity to gamma, beta, and X-ray radiation and determined that the error range in the response linearity is less than 3% with regard to radiation strength and in the detection accuracy evaluation with regard to measured distance using MCNPX Code. We hope that the results of this study will contribute to cost savings for radiation detection system configuration and to individual exposure management.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.661-668
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• 2018

Biomedical signals using skin resistance have different characteristics according to stress diseases. Biological diagnostic devices for diagnosing stress diseases have been developed by using these characteristics, and devices have been developed so that the signals measured by the skin storage meter can be easily analyzed. Experts in the field will look directly at the output signal to determine the likelihood of any stress disorder. However, it is very difficult for a person to accurately determine whether a person to be measured has a stress disorder by analyzing a bio-signal measured by each person to be measured, and the result of the judgment is very likely to be wrong. In order to solve these problems, we implemented the function of determining the signal of a stress disorder by using the machine learning technique. SVM was used as a classification method in consideration of low computing ability of measurement equipment. Training data and test data were randomly generated for each disease using error range 5 based on 13 diseases. Simulation results showed more than 90% decision accuracy. In the future, if the measurement equipment is actually applied to the patients, we can retrain the classifier with the newly generated data.