• The Korean Journal of Nuclear Medicine
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• v.32 no.5
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• pp.414-424
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• 1998

Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of the Korean Society of Food Science and Nutrition
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• v.32 no.1
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• pp.35-41
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• 2003

The study was conducted to develope a rapid method for the detection of Yersinia enterocolitica in spring water and vegetables via multiplex polymerase chain reaction (PCR) technique using ail, yst, uirF and subgenus-specific Y16S primers. Specificity and sensitivity of multiplex PCR and application of best primers for the detection of Y. enterocolitica from spring water and vegetables were investigeted. Y. enterocolitica ATCC 27729 strains gave 356 bP and 200 bp (Y16S) and 134 bp (yst) bands. but Y. enterocolitica ATCC 9610 and ATCC 23715 strains gave 200 bp and 134 bp bands.In the meanwhile, non-pathogenic Yersinia species, such as Y. frederikseni, Y. inter-media, Y. kristenseni and Y. pseudotuberculosis gave only single 200 bp band, and other bacteria including Escherichia coli O157:H7 ATCC 25392, Shigella dysenteri. Staphylococcu aureus ATCC 25923 and Listeria mo-nocytogenes ATCC 19111 did not show any bands. Among primers, yst and Y16S primer showed the best sensitivity. Seven CFU/mL Y. enterocolitica cells could be detected with yst and Y16S primers and the sensitivity was significantly improved by the further 2nd PCR after 38 cycles of first PCR amplication. Spring water, cabbage and mushroom were inoculated with Y. enterocolitica to determine the sensitivity of multiplex-PCR for the rapid detection of Y. enterocolitica. Multiplex-PCR assay could detect 7 or 70 cells in spring water and vegetables using whole cell lysate with repeating PCR amplication.

• Tunnel and Underground Space
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• v.13 no.5
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• pp.373-388
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• 2003

The investigation on the rock discontinuity geometry has been usually undergone by direct measurement on the rock exposures. But this sort of field work has disadvantages, which we, for example, restriction of surveying areas and consuming excessive times and labors. To cover these kinds of disadvantages, image processing could be regarded as an altemative way, with additional advantages such as automatic and objective tools when used under adequate computerized algorithm. This study was focused on the recognition of the rock discontinuities captured in the image of rock exposure by digital camera and the production of the discontinuity map automatically. The whole process was written using macro commands builtin image analyzer, ImagePro Plus. ver 4.1(Media Cybernetic). The procedure of image processing developed in this research could be divided with three steps, which are enhancement, recognition and extraction of discontinuity traces from the digital image. Enhancement contains combining and applying several filters to remove and relieve various types of noises from the image of rock surface. For the next step, recognition of discontinuity traces was executed. It used local topographic features characterized by the differences of gray scales between discontinuity and rock. Such segments of discontinuity traces extracted from the image were reformulated using an algorithm of computer decision-making criteria and linked to form complete discontinuity traces. To verify the image processing algorithms and their sequences developed in this research, discontinuity traces digitally photographed on the rock slope were analyzed. The result showed about 75～80% of discontinuities could be detected. It is thought to be necessary that the algorithms and computer codes developed in this research need to be advanced further especially in combining digital filters to produce images to be more acceptable for extraction of discontinuity traces and setting seed pixels automatically when linking trace segments to make a complete discontinuity trace.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.529-542
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• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• Journal of Life Science
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• v.25 no.8
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• pp.903-909
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• 2015

Loop-mediated isothermal amplification (LAMP), a PCR-based diagnostic method, is based on autocycling strand displacement DNA synthesis in the presence of exonuclease-negative Bst DNA polymerase under isothermal conditions. With the help of four specific primers that recognize six different sequences of a target DNA, LAMP has high specificity in pathogenic identification in a short time. Hence, in the present study, LAMP is used as a diagnostic tool in the identification of the most dreadful aquatic pathogenic species, Vibrio alginolyticus, and to develop species-specific LAMP primers and optimization of LAMP reaction conditions such as annealing temperature, elongation time, and other PCR chemical concentrations, including MgSO₄, dNTPs, Betaine, and Bst polymerase. The optimized LAMP primers were also checked for specificity with other Vibrio species, which showed that the designed primers were very specific to V. alginolyticus After the first introduction of a species name like this one, the first part (“Vibrio” in this case) should be abbreviated to only the first letter.only. These are usually the most harmful pathogens of the Vibrio species that appear in shrimp and crabs. The results also revealed that the LAMP assay could be 10-fold more sensitive than conventional PCR in detecting V. alginolyticus. This could be the first report on using a rapid and highly sensitive technique, the LAMP assay, in the effective diagnosis of the pathogenic bacteria V. alginolyticus, which could help in the early detection of diseases, particularly in aquaculture.

• Economic and Environmental Geology
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• v.48 no.4
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• pp.325-335
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• 2015

This study examined the possibility to extract potential alteration zones and lithologic information based on ASTER band ratio techniques for mineralized area located in ${\ddot{O}}v{\ddot{o}}rkhangai$ province, Mongolia, and the effectiveness of remote sensing as a preliminary exploration tool for mineral exploration was tested. The results of ABRLO, PBRLO, and PrBRLO models indicated that the detection of argillic zone requires the verification of the samples to verify hydrothermal alteration minerals as clay minerals can formed by weathering process, whereas phyllic-propylitic zones were considerably related to the spatial distribution of the intrusive bodies, geological structures, and ore distribution. QI and MI results showed that QI is more useful for sedimentary rocks such as conglomerate and sandstone than meta-sedimentary like quartzite, and MI faced relatively uncertain in detection of felsic or mafic silicate rocks. QI and MI may require additional geologic information such as the characteristics of samples and geological survey data to improve extraction of lithologic information, and, if so, it is expected that remote sensing technique would contribute significantly as a preliminary geological survey method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.33-40
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• 2005

This paper presents a structure of the searcher using a diversity in array antenna systems operating in the cdma2000 1x signal environments. The new technique exploits the fact that the In-phase and quadrature components of interferers can respectively be viewed as an independent gaussian noise at each antnna element in most practical cdma signal environments. The proposed PN acquisition scheme is a singles-dwell PN acquisition system consisting of two stages, that is, the searching stage and the verification stage. The searching stage independently correlates the receiver multiple signals with PN generator of each antenna element for obtaining the synchronous energy at the entire region. Then, the searching results of each antenna element are non-coherently combinind. The verification stage compares the searching energy with the optimal threshold, which is predesigned in the lock detector, and decides whether the acquisition is successful or fail. In this paper, we analyzed the effect of tile diversity order to determine the mean acquisition time. In general, it is known that the mean acquisition time significantly decrease as the number of antenna elements increases. But, as the diversity order goes up, the enhancement of the performance is saturated. Therefore, to decrease the mean acquisition time of the searcher, we must design the optimal array antenna systems by considering the operating SNR range of the receiver, the probability of detection $P_D$ and that of false alarm $P_{FA}$ . The Performance of the proposed PN acquisition scheme is analyzed in frequency selective Rayleigh fading channels. In this paper, the effect of the number of antenna elements on PN acquisition scheme is shown according to the probability of detection $P_D$ and that of false alarm $P_{FA}$.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5385-5389
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• 2012

Introduction: Sentinel lymph node biopsy (SLNB) is a precise procedure for lymphatic staging in early breast cancer. In a valid SLNB procedure, axillary lymph node dissection (ALND) can be omitted in nodenegative cases without compromising patient safety. In this study, detection rate, accuracy and false negative rate of SLNB for breast cancer was evaluated in a setting with simple modified conventional pathology facilities without any serial sectioning or immunohistochemistry. Material and Medthod: Patients with confirmed breast cancer were enrolled in the study. SLNB and ALND were performed in all cases. Lymph node metastasis was evaluated in SLN and in nodes removed by ALND to determine the false negative rate. Pathologic assessment was carried out only by modified conventional technique with only 3 sections. Detection rate was determined either by lymphoscintigraphy or during surgery. Results: 78 patients with 79 breast units were evaluated. SLN was detected in 75 of 79 cases (95%) in lymphoscintigraphy and 76 of 79 cases (96%) during surgery. SLN metastases was detected in 30 of 75 (40%) cases either in SLNB and ALND groups. Accuracy of SLNB method for detecting LN metastases was 92%. False negative rate was 3 of 30 of positive cases: 10%. In 7 of 10 cases with axillary lymphadenopathy, LN metastastates was detected. Conclusion: SLNB is recommended for patients with various tumor sizes without palpable lymph nodes. In modified conventional pathologic examination of SLNs, at least macrometastases and some micrometastases could be detected similar to ALND. Consequently, ALND could be omitted in node-negative cases with removal of all palpable LNs. We conclude that SLNB, as one of the most important developments in breast cancer surgery, could be expanded even in areas without sophisticated pathology facilities.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.81-89
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• 2017

In this paper, we propose a gait pattern recognition method for intelligent prosthesis that enables walking in various environments of femoral amputees. The proposed gait mode changing method is a single sensor based algorithm which can discriminate gait surface and gait phase using only strain gauges sensor, and it is designed to simplify the algorithm based on multiple sensors of existing intelligent prosthesis and to reduce cost of prosthesis system. For the recognition algorithm, we analyzed characteristics of the ground reaction force generated during gait of normal person and defined gait step segmentation and gait detection condition, A gait analyzer was constructed for the gait experiment in the environment similar to the femoral amputee. The validity of the paper was verified through the defined detection conditions and fabricated instruments. The accuracy of the algorithm based on the single sensor was 95%. Based on the proposed single sensor-based algorithm, it is considered that the intelligent prosthesis system can be made inexpensive, and the user can directly grasp the state of the walking surface and shift the walking mode. It is confirmed that it is possible to change the automatic walking mode to switch the walking mode that is suitable for the walking mode.