• The Korean Journal of Nuclear Medicine
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• v.38 no.4
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• pp.288-293
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• 2004

Purpose: increased uptake of wrist and hand joints in three phase bone scintigraphy (TPBS) have been used in the detection of reflex sympathetic dystrophy syndrome (RSDS). TPBS frequently shows increased shoulder uptake in the hemiplegic RSDS patients. We investigated the significance of the shoulder uptake in the detection of these patients. Materials and Methods: Twenty three patients who had hemiplegia due to brain stroke and diagnosed as RSD were enrolled in this study (M:F=16:7, R:L=11:12). The mean age was $63{\pm}10$ yrs. Ter normal volunteer (mean age: $60{\pm}5$, M:F=1:9) data was used as control group. TPBS was performed $59{\pm}32$ days after stoke (acute stage). We obtained the count ratios of bilateral hands by drawing a region of interest (ROI) in three phase images and compared to the count ratios of shoulders in the delayed image. Hand ROI included an ipsilateral wrist. Sensitivity of detecting the affected limb was defined using the right/left count ratio of normal control. Results: Sensitivities using count ratios of hand blood flow, blood pool and delayed image were 45%, 76% and 78%, respectively. Sensitivity of shoulder count ratio was 74%. Log of right/left counts of hand delayed image and that of shoulder delayed image were correlated well with statistical significance (Spearman's R=0.824, p<0.001). Conclusion: Shoulder uptake showed good correlation with hand uptake in the delayed image of TPBS. Shoulder uptake maybe helpful in the diagnosis of reflex sympathetic dystrophy syndrome in patients with hemiplegia.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.358-366
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• 2012

Cirrhosis is a consequence of chronic liver disease characterized by replacement of liver tissue by fibrosis, scar tissue and regenerative nodules leading to loss of liver function. Liver Cirrhosis is most commonly caused by alcoholism, hepatitis B and C, and fatty liver disease, but has many other possible causes. Some cases are idiopathic disease from unknown cause. Abdomen of liver Computed tomography(CT) is one of the primary imaging procedures for evaluating liver disease such as liver cirrhosis, Alcoholic liver disease(ALD), cancer, and interval changes because it is economical and easy to use. The purpose of this study is to detect technique for computer-aided diagnosis(CAD) to identify liver cirrhosis in abdomen CT. We experimented on the principal components analysis(PCA) algorithm in the other method and suggested texture information analysis(TIA). Forty clinical cases involving a total of 634 CT sectional images were used in this study. Liver cirrhosis was detected by PCA method(detection rate of 35%), and by TIA methods(detection rate of 100%-AGI, TM, MU, EN). Our present results show that our method can be regarded as a technique for CAD systems to detect liver cirrhosis in CT liver images.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.46-48
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• 2016

Purpose The liver one of the most common site for distant metastasis for a variety of tumor, especially of gastrointestinal origin. the purpose of this study was to analyze image quality between standard scan and additional liver scan. Materials and Methods From September 2015 to February 2016. 152 patients were examined undergo gastrointestinal cancer. 32 patients confirmed liver metastasis analyzed same liver ROI level and check the SNR, SUV and T/N ratio Results The $SNR_{mean}$ of standard was $17.7{\pm}10.3$; addition was $22.3{\pm}9.7$ (p<0.05). In $SUV_{max}$ of standard was $6.7{\pm}2.8$; addition was $7.6{\pm}3.2$ (P<0.05). and the T/N ratio of standard was $2.1{\pm}0.6$; addition was $2.5{\pm}0.8$ (P<0.05). Conclusion The $SNR_{mean}$, $SUV_{max}$ and T/N ratio were higher than those on the first scan (P<0.05). The SNRmean showed the highest change rate among the parameters. A additional liver scan is more favorable for the detection of gastrointestinal cancer patients.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.507-515
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• 2015

This paper suggests 6 cases of TFA parameters algorithm(Mean, VA, RS, SKEW, UN, EN) to search for the detection of recognition rates regarding breast disease using CAD on ultrasound images. Of the patients who visited a university hospital in Busan city from August 2013 to January 2014, 90 cases of breast ultrasound images based on the findings in breast US and pathology were selected. $50{\times}50$ pixel size ROI was selected from the breast US images. After pre-processing histogram equalization of the acquired test images(negative, benign, malignancy), we calculated results of TFA algorithm using MATLAB. As a result, in the TFA parameters suggested, the disease recognition rates for negative and malignancy was as high as 100%, and negative and benign was approximately 83~96% for the Mean, SKEW, UN, and EN. Therefore, there is the possibility of auto diagnosis as a pre-processing step for a screening test on breast disease. A additional study of the suggested algorithm and the responsibility and reproducibility for various clinical cases will determine the practical CAD and it might be possible to apply this technique to range of ultrasound images.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.303-310
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• 2013

Thyroid nodular disease is the most frequently appeared in thyroid disease. Thyroid ultrasonography offers location of nodules, size, the number, information of internal echo characteristic. Thus, it makes possible to sort high-risk nodule containing high possibility about thyroid cancer and to induct precisely when take a Fine Needle Biopsy Aspiration. On thyroid nodule, the case which is diagnosed as malignant is less than 5% but screening test is very important on ultrasound and also must be reduced unnecessary procedure. Therefore, in this study an approach for describing a region is to quantity its texture content. We applied TFA algorithm on case which has been pathologically diagnosed as papillary thyroid cancer. we obtained experiment image which set the ROI on ultrasound and cut the $50{\times}50$ pixel size, histogram equalization. Consequently, Disease recognition detection efficiency of GLavg, SKEW, UN, ENT parameter were high as 91~100%. It is suggestion about possibility on CAD which distinguishes thyroid nodule. In addition, it will be helpful to differential diagnosis of thyroid nodule. If the study on additional parameter algorithm is continuously progressed from now on, it is able to arrange practical base on CAD and it is possible to apply various disease in the thyroid US.

• Investigative Magnetic Resonance Imaging
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• v.19 no.3
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• pp.162-167
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• 2015

Purpose: To evaluate the usefulness of quantitative analysis of the facial nerve using contrast-enhanced three-dimensional (CE 3D) fluid-attenuated inversion recovery-volume isotopic turbo spin echo acquisition (FLAIR-VISTA) for the diagnosis of Bell's palsy in pediatric patients. Materials and Methods: Twelve patients (24 nerves) with unilateral acute facial nerve palsy underwent MRI from March 2014 through March 2015. The unaffected sides were included as a control group. First, for quantitative analysis, the signal intensity (SI) and relative SI (RSI) for canalicular, labyrinthine, geniculate ganglion, tympanic, and mastoid segments of the facial nerve on CE 3D FLAIR images were measured using regions of interest (ROI). Second, CE 3D FLAIR and CE T1-SE images were analyzed to compare their diagnostic performance by visual assessment (VA). The sensitivity, specificity, and accuracy of RSI measurement and VA were compared. Results: The absolute SI of canalicular and mastoid segments and the sum of the five mean SI (total SI) were higher in the palsy group than in the control group, but with no significant differences. The RSI of the canalicular segment and the total SI were significantly correlated with the symptomatic side (P = 0.028 and 0.015). In 11/12 (91.6%) patients, the RSI of total SI resulted in accurate detection of the affected side. The sensitivity, specificity, and accuracy for detecting Bell's palsy were higher with RSI measurement than with VA of CE 3D FLAIR images, while those with VA of CE T1-SE images were higher than those with VA of CE 3D FLAIR images. Conclusion: Quantitative analysis of the facial nerve using CE 3D FLAIR imaging can be useful for increasing the diagnostic performance in children with Bell's palsy when difficult to diagnose using VA alone. With regard to VA, the diagnostic performance of CE T1-SE imaging is superior to that of CE 3D FLAIR imaging in children. Further studies including larger populations are necessary.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.103-112
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• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.441-447
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• 2023

Intravenous infusion therapy is a standard nursing procedure in medical institutions that provides patients with drugs, fluids, blood, and nutrients into the patient's mucus. It is mainly performed and managed by nurses. Additionally, it is an injection method that injects drugs directly into the blood vessels, and is used to achieve rapid results in emergency situations, and quick and accurate effects can be expected. Even experienced nurses through education and training often make mistakes, which can not only cause discomfort to patients but also cause various problems that threaten patient safety. Various studies are being conducted to reduce the pain caused by these mistakes. This paper acquired images of veins on the back of the hands of three subjects through an image detection device and conducted a study to derive an algorithm to provide clear vein images through image processing of the collected images. To sharpen the acquired vein images, existing algorithms Histogram Equalization, CLAHE, and Unsharp Masking were selected and combined. A histogram graph was used to compare images derived by applying individual algorithms and algorithm combinations to images. The histogram graph was checked by calculating the difference between the minimum and maximum values of distributed pixels and averaging them. The algorithm combination presented in this paper was 209.1, which was higher than the average values of individual algorithms of 138.7, 132.3, and 126.2, and it was confirmed that visibility was good even in actual images.

• Progress in Medical Physics
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• v.24 no.2
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• pp.85-91
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• 2013

At present, megavoltage computed tomography (MVCT) is the only method used to correct the position of tomotherapy patients. MVCT produces extra radiation, in addition to the radiation used for treatment, and repositioning also takes up much of the total treatment time. To address these issues, we suggest the use of a video image-guided setup (VIGS) system for correcting the position of tomotherapy patients. We developed an in-house program to correct the exact position of patients using two orthogonal images obtained from two video cameras installed at $90^{\circ}$ and fastened inside the tomotherapy gantry. The system is programmed to make automatic registration possible with the use of edge detection of the user-defined region of interest (ROI). A head-and-neck patient is then simulated using a humanoid phantom. After taking the computed tomography (CT) image, tomotherapy planning is performed. To mimic a clinical treatment course, we used an immobilization device to position the phantom on the tomotherapy couch and, using MVCT, corrected its position to match the one captured when the treatment was planned. Video images of the corrected position were used as reference images for the VIGS system. First, the position was repeatedly corrected 10 times using MVCT, and based on the saved reference video image, the patient position was then corrected 10 times using the VIGS method. Thereafter, the results of the two correction methods were compared. The results demonstrated that patient positioning using a video-imaging method ($41.7{\pm}11.2$ seconds) significantly reduces the overall time of the MVCT method ($420{\pm}6$ seconds) (p<0.05). However, there was no meaningful difference in accuracy between the two methods (x=0.11 mm, y=0.27 mm, z=0.58 mm, p>0.05). Because VIGS provides a more accurate result and reduces the required time, compared with the MVCT method, it is expected to manage the overall tomotherapy treatment process more efficiently.