• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.90-101
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• 1997

The purpose of this study is to evaluate the diagnostic accuracy of various quantitative indices for the differentiation of benign from malignant primary soft tissue tumors by FDG-PET. A series of 32 patients with a variety of histologically or clinically confirmed benign (20) or malignant (12) soft tissue lesions were evaluated with emission whole body (5min/bed position) PET after injection of [$^{18}F$]FDG. Regional 20min transmission scan for the attenuation correction and calculation of SUV was performed in 16 patients (10 benign, 6malignant) followed by dynamic acquisition for 56min. Postinjection transmission scan for the attenuation correction and calculation of SUV was executed in the other 16 patients (10 benign, 6 malignant). The following indices were obtained. the peak and average SUV (pSUV, aSUV) of lesions, tumor-to-background ratio acquired at images of 51 min p.i. ($TBR_{51}$), tumor-to-background ratio of areas under time-activity curves ($TBR_{area}$) and the ratio between the activities of tumor ROI at 51 min p. i. and at the time which background ROI reaches maximum activity on the time-activity curves ($T_{51}/T_{max}$). The pSUV, aSUV, $TBR_{51}$, and $TBR_{area}$ in malignant lesions were significantly higher than those in benign lesions. We set the cut-off values of pSUV, aSUV, $TBR_{51},\;TBR_{area}$ and $T_{51}/T_{max}$ for the differentiation of benign and malignant lesions at 3.5, 2.8, 5.1, 4.3 and 1.55, respectively. The sensitivity, specificity and accuracy were 91.7%, 80.0%, 84.4% by pSUV and aSUV, 83.3%, 85.0%, 84.4% by $TBR_{51}$, 83.3%, 100%, 93.8% by $TBR_{area}$ and 66.7%, 70.0%, 68.8% by $T_{51}/T_{max}$. The time-activity curves did not give additional information compared to SUV or TBR. The one false negative was a case with low-grade fibrosarcoma and all four false positives were cases with inflammatory change on histology. The visual, analysis of FDG-PET also detected the metastatic lesions in malignant cases with comparable accuracy In conclusion, all pSUV, aSUV, $TBR_{51}$, and $TBR_{area}$ are useful metabolic semi-quantitative indices with good accuracy for the differentiation of benign from malignant soft-tissue lesions.

• The Korean Journal of Nuclear Medicine
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• v.33 no.1
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• pp.76-83
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• 1999

Purpose: We performed this study to compare T1-201 and Tc-99m MIBI scans for the differentiation of malignant from benign breast mass. Materials and Methods: Thirty-eight female patients underwent T1-201 breast scan and thirty-two of them also underwent Tc-99m MIBI scan of the breast. After intravenous injection of 74-111 MBq of T1-201, early (10 minutes) and delayed (3 hours) images were obtained. Then, 555-740 MBq of Tc-99m MIBI was injected and images after 30 minutes were obtained. We compared T1-201 and Tc-99m MIBI scans with pathologic results. Results: Twenty-three patients were confirmed to have infiltrating duct carcinoma and fifteen patients to have benign breast mass by excisonal biopsy. The sensitivity of early and delayed T1-201 scan and Tc-99m MIBI scan in the detection of malignant breast lesion were 100% (23/23), 82% (18/22), and 90% (18120), respectively. The sensitivity of early T1-201 scan was significantly higher than that of delayed T1-201 scan (p<0.05). The specificity of early and delayed T1-201 scan and Tc-99m MIBI scan were 73% (l1/15), 73% (l1/15) and 83% (10/12), respectively (p: not significant). Three patients out of nine with fibroadenoma and one patient with atypical duct hyperplasia were false positive in both early and delayed T1-201 scans. The size of fibroadenoma with false positive in early and delayed T1-201 scan (4 cases) was larger than that of 11 fibroadenoma with true negative scan (p<0.01). Metastatic axillary lymph node involvement was present in fifteen patients. The sensitivity to detect metastatic nodes was 38% (5/13) for early T1-201 images, 15% (2/13) for delayed T1-201 images, 58% (7/12) for Tc-99m MIBI planar images and 67% (4/6) for Tc-99m MIBI SPECT. The sensitivity of Tc-99m MIBI planar or SPECT was significantly higher than that of delayed T1-201 images (p<0.05). Conclusion: Early T1-201 and Tc-99m MIBI scan are useful noninvasive methods to differentiate malignant from benign mass of breast Tc-99m MIBI scan was sensitive in detecting axillary lymph node metastasis in patients with breast cancer.

• Tuberculosis and Respiratory Diseases
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• v.47 no.3
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• pp.311-320
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• 1999

Background: In recent years, tuberculosis has re-emerged as a major health problem in both industrialized & developing countries. Recent advances in identifying & purifying antigens secreted in active tuberculosis infection have lead to the development of serological assays based on a number of immunodominant antigens. To date, the most sensitive and specific of these antigens has been the 38-kDa antigen. Method: Two rapid membrane-based serologic assays using antigen(38-kDa) from mycobacterium tuberculosis for the diagnosis of tuberculosis were evaluated in 22 patients with smear-positive pulmonary tuberculosis, 14 patients with inactive pulmonary tuberculosis, and 9 patients with non-tuberculous lung disease. Result: The evaluation of validity(sensitivity, specificity, positive predictive value, negative predictive value, false positivity and false negativity) of STAT-PAK ULTRA FAST$^{(R)}$ were 77.3%, 28.6%, 63.0%, 44.4%, 71.4 %, and 22.7% for differential diagnosis of active pulmonary tuberculosis and inactive pulmonary tuberculosis, respectively. The evaluation of validity of STAT-PAK ULTRA FAST$^{(R)}$ were 77.3%, 33.3%, 73.9%, 37.5%, 66.7%, and 22.7% for differential diagnosis of active pulmonary tuberculosis and non-tuberculosis. The evaluation of validity of ICT Tuberculosis$^{(R)}$ were 54.5%, 57%, 66.7%, 44.4%, 42.9%, and 45.5% for differential diagnosis of active pulmonary tuberculosis and inactive pulmonary tuberculosis. The evaluation of validity of ICT Tuberculosis$^{(R)}$ were 54.5%, 100%, 100%, 47.4%, 0%, and 45.4% for differential diagnosis of active pulmonary tuberculosis and non-tuberculosis. Conclusion: We concluded no effectiveness of STAT-PAK ULTRA FAST$^{(R)}$ & ICT tuberculosis$^{(R)}$on serologic diagnosis of pulmonary tuberculosis. In the future, further large-scale study should be needed for serologic diagnosis of pulmonary tuberculosis.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Laboratory Medicine and Quality Assurance
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• v.40 no.2
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• pp.51-69
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• 2018

As part of the immunoserology program of the Korean Association of External Quality Assessment Service, we organized two trials on the external quality assessment of hepatitis viral markers in 2016 and 2017. The hepatitis viral antigens and antibodies program consisted of 10 test items. We delivered two and three types of pooled sera specimens to 965 and 965 institutions for the first and second trials of external proficiency testing in 2016, respectively. The number of participating laboratories was 915 (94.8%) and 913 (95.0%) in the first and second trials in 2016, respectively. We also delivered three kinds of pooled sera specimens to 936 and 1,015 institutions for the first and second trials of external proficiency testing in 2017, respectively. The number of participating laboratories was 920 (98.3%) and 996 (98.1%) in the first and second trials in 2017, respectively. The most commonly tested items were hepatitis B surface antigen, followed by the antibodies to hepatitis B surface antigen, anti-hepatitis C virus, hepatitis B envelope antigen, antibodies to hepatitis B envelope antigen, anti-hepatitis A virus and antibodies to hepatitis B core antigen. The most frequently used methods for detecting viral markers were the chemiluminescence immunoassay and the electrochemiluminescence immunoassay, but they yielded a few-false positive results due to the matrix effect. The immunochromatographic assay yielded false-negative results for anti-hepatitis A virus due to low sensitivity. Continuous improvement in the quality of viral hepatitis testing through participation in the survey seems necessary.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.637-656
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• 2023

River estuaries are dynamic and productive ecosystems with high regional biodiversity. Environmental DNA (eDNA) has become a useful approach to assessing biodiversity in aquatic ecosystems. This study was conducted to investigate fish community characteristics and species diversity in two river estuary ecosystems, the Taehwa River and Changwon Stream. We further compared conventional and eDNA metabarcoding analyses of the fish communities. The conventional survey was performed in May, July, and October 2022, while the eDNA analysis was conducted only in May. We observed various fish species with different life histories, including carp, goby, and marine fish. We also found that migratory fish, such as dace Tribolodon hakonensis, sweetfish Plecoglossus altivelis, and eel Auguilla japonica, occurred in the Taehwa River, suggesting high river connectivity. Marine fish species were predominant in the Changwon Stream, as this river is located close to the sea. The diversity indices showed that the Taehwa River generally had higher species richness, evenness, and diversity values than the Changwon Stream. A total of 9-19 species were detected in the conventional survey for the three sites, whereas 11-18 species were found from eDNA analysis. The findings indicate that the sensitivity of eDNA was similar to or higher than that of the conventional method. Our study findings suggest the efficiency and efficacy of eDNA-based fish community monitoring, although with some shortcomings in applying the genetic marker to Korean fish, including no clear-cut distinction for Korean endemic species and/or genetically closely related species groups.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Parasites, Hosts and Diseases
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• v.30 no.2
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• pp.141-146
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• 1992

A total of 197 fecal specimens was prepared for quantitative examination of helminth eggs by modified Kato's cellophane thick smear (M.C.T.S.) and Stoll's dilution egg counting technique (D.E,C.T.). The comparative effectiveness of two techniques was evaluated and conversion function was deduced. The average time required for the microscopic examination on one slide by M.C.T.S. was 12.6 minutes and that of D.E.C.T. was 14.6 minutes. M.C.T.S. showed lower false negative rate than D.E.C.T in light worm burden cases. Functions to convert the counts obtained by M.C.T.S. to E.P.G. by Stoll's dilution egg counting technique were $47.86{\times}10^{0.87{\;}logM.C.T.S.},{\;}$ in A. lumbricoides, $41.69{\times}10^{0.82{\;}logM.C.T.S.}$ in T. trichiura and $63.10{\times}10^{0.85{\;}logM.C.T.S.}$ in C. sinensis. It was suggested M.C.T.S. be better than D.E.C.T. for the quantitative examination of intestinal helminthiases such as A. lumbricoides, T. trichiura, and C. sinensis infections even in the cases with low worm burden.

• Journal of radiological science and technology
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• v.31 no.2
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• pp.141-147
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• 2008

Thyroid nodules are a common disease in clinical practice. Fine needle aspiration (FNA) is an accurate and safe method for the diagnosis of thyroid nodules. One of the limitations of FNA is the variable rate of unsatisfactory specimens, especially in small sized, deep seated or complex cystic nodules. To overcome this problem, ultrasound-guided FNA (US-FNA) has been widely used. In this study, the clinical usefulness of US-FNA cytology in thyroid nodules was investigated. Female to male ratio was 6.58:1. The incidence of nodules were 157 (43.1%) cases on the right, 130 (35.7%) cases on the left and 9 (2.5%) cases in isthmus. Total 139 cases (38.2%) belong to less than 1cm and 225 cases (61.8%) belong to more than 1cm. As for the echo type in the nodules, solid types were 255(70.1%), cystic type 39 (10.7%) cases, and the percentage of mixed type was 19.2%. The results show that US-FNA reduces the possibility of unsatisfactory cytologic specimens and the rate of false-negative diagnosis, and improves the diagnostic accuracy in investigation thyroid nodules.

• Biomedical Science Letters
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• v.17 no.3
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• pp.191-196
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• 2011

Noroviruses (noroV) are the major cause of nonbacterial gastroenteritis in humans worldwide. Since noroV cannot yet be cultured in vitro and their diagnosis by electron microscopy requires at least $10^6$ viral particles/g of stool a variety of molecular detection techniques represent an important step towards the detection of noroV. In the present study, we have applied real-time nucleic acid sequence-based amplification (real-time NASBA) for simultaneous detection of NoroV genogroup I (GI) and genogroup II (GII) using standard viral RNA. For real-time NASBA assay which can detected noroV GI and GII, a selective region of the genes encoding the capsid protein was used to design primers and genotype-specific molecular beacon probes. The specificity of the real-time NASBA using newly designed primers and probes were confirmed using standard viral RNA of noroV GI and GII. To determine the sensitivity of this assay, serial 10-fold dilutions of standard viral RNA of noroV GI and GII were used for reverse transcription polymerase chain reaction (RT-PCR) and real-time NASBA. The results showed that while agarose gel electrophoresis could detect RT-PCR products with 10 pg of standard viral RNA, the real-time NASBA assay could detect 100 fg of standard viral RNA. These results suggested that the real-time NASBA assay has much higher sensitivity than conventional RT-PCR assay. This assay was expected that might detect the viral RNA in the specimens which could have been false negative by RT-PCR. There were needed to perform real-time NASBA with clinical specimens for evaluating accurate sensitivity and specificity of this assay.