• Title/Summary/Keyword: diagnostic software

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An Integration of Legacy Nuclear Simulation Code into HLA Federation using Shared Memory (공유메모리를 사용한 레거시 원자력 시뮬레이션 코드의 HLA 패더레이션으로의 통합)

  • Park Geun-Ok;Han Kwan-Ho;Lim Jong-Tae
    • The KIPS Transactions:PartD
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    • v.12D no.5 s.101
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    • pp.797-806
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    • 2005
  • The objective of the In-h(High Level Architecture) have recommended by DoD(Department of Defense) is to facilitate interoperability among simulations and to promote reuse of their components. There are many legacy simulation softwares developed before the HLA becomes simulation standard. The integration of legacy simulations into federations using the HLA is an important research topic in M&S(Modeling and Simulation) area. Legacy simulation softwares of the mission critical industry such as nuclear and aerospace are generally use Fortran language. However, the reuse of those is not easy because the HLA is not support Fortran language. This paper suggests a integration method which minimizes the modification of legacy simulation software and migrates the legacy simulation software to HLA federation. Each federate participating in federation have the separated executables that communicate via a shared memory created at run-time. Two types of shared memory blocks are used for publication and subscription. Declaration block for global variables used in legacy simulation software is separated for publication and subscription and then mapped as classes of objects and interactions for the HLA FOM design. To validate the suggested method, we approached the HLA integration of legacy nuclear simulation code being used in plant design and to observe the integration results, we used the FMT(Federation Management Tool). The diagnostic information which the FTM displays showed that our method can be successfully and effectively used for a HLA federation.

Classification of Urinary Stone into Uric Acid & Non-uric Acid by Dual-Energy (이중에너지 전산화단층촬영을 이용한 요로결석의 성분 분석에 관한 연구)

  • Myung-Jin Jung;Sung-Gil Kim
    • Journal of the Korean Society of Radiology
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    • v.17 no.6
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    • pp.835-841
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    • 2023
  • The aim of this study is to evaluate the diagnostic ability of dual-energy computed tomography (DECT) for Composition determination of urinary stones in phantom model. Seventeen cases with urinary stones who underwent DECT were enrolled in the study. The composition of the urinary stones was extracted from the seventeen patients were analyzed with DECT in phantom model with fresh pork. The volume scan method using Dual-energy software was used and the scanned image sets were assessed. All 17 urinary stones of the phantom model were analyzed according to the stone composition using DE stone Analysis were divided into uric acid stones (n=6, 35.29%) and non-uric acid stones (n=11, 64.71%). These urinary stones were pathologically confirmed. The mean attenuation values of uric acid stones at 135 kV, 100 kV and 80 kV was 348.87 ± 166.37 HU, 345.33 ± 151.18 HU and 337.94 ± 172.77 HU, respectively. The mean attenuation values of non-uric acid stones at 135 kV, 100 kV and 80 kV was 551.93 ± 297.09 HU, 747.04 ± 351.31 HU and 958.19 ± 424.72 HU, respectively. At 80 kV, uric acid stones and non-uric acid stones showed significant difference in the attenuation values(P<0.05). The attenuation values of DECT could differentiate the compositions of urinary stones between uric acid and non-uric acid stones at 80 kV in phantom model.

Current Status of Imaging Physics & Instrumentation In Nuclear Medicine (핵의학 영상 물리 및 기기의 최신 동향)

  • Kim, Hee-Joung
    • Nuclear Medicine and Molecular Imaging
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    • v.42 no.2
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    • pp.83-87
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    • 2008
  • Diagnostic and functional imaging device have been developed independently. The recognition that combining of these two devices can provide better diagnostic outcomes by fusing anatomical and functional images. The representative examples of combining devices would be PET/CT and SPECT/CT. Development and their applications of animal imaging and instrumentation have been very active, as new drug development with advanced imaging device has been increased. The development of advanced imaging device resulted in researching and developing for detector technology and imaging systems. It also contributed to develop a new software, reconstruction algorithm, correction methods for physical factors, image quantitation, computer simulation, kinetic modeling, dosimetry, and correction for motion artifacts. Recently, development of MRI and PET by combining them together was reported. True integration of MRI and PET has been making the progress and their results were reported. The recent status of imaging and instrumentation in nuclear medicine is reported in this paper.

Magnetic Resonance Elastography (자기 공명 탄성법)

  • Kim, Dong-Hyun;Yang, Jae-Won;Kim, Myeong-Jin
    • Investigative Magnetic Resonance Imaging
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    • v.11 no.1
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    • pp.10-19
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    • 2007
  • Conventional MRI methods using T1-, T2-, diffusion-, perfusion-weighting, and functional imaging rely on characterizing the physical and functional properties of the tissue. In this review, we introduce an imaging modality based on measured the mechanical properties of soft tissue, namely magnetic resonance elastography (MRE). The use of palpation to identify the stiffness of tissue remains a fundamental diagnostic tool. MRE can quantify the stiffness of the tissue thereby providing a objective means to measure the mechanical properties. To accomplish a successful clinical setting using MRE, hardware and software techniques in the area of transducer, pulse sequence, and imaging processing algorithm need to be developed. Transducer, a mechanical vibrator, is the core of MRE application to make wave propagate invivo. For this reason, considerations of the frame of human body, pressure and friction of the interface, and high magnetic field of a MRI system needs to be taken into account when designing a transducer. Given that the wave propagates through human body effectively, developing an appropriate pulse sequence is another important issue in obtaining an optimal image. In this review paper, we introduce the technical aspects needed for MRE experiments and introduce several applications of this new field.

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Development of Imaging Gamma Probe Using the Position Sensitive PMTube (위치 민감형 광전자증배관을 이용한 영상용 감마프로브의 개발)

  • Bong, Jeong-Gyun;Kim, Hui-Jung;So, Su-Gil;Kim, Han-Myeong;Lee, Jong-Du;Gwon, Su-Il
    • Journal of Biomedical Engineering Research
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    • v.20 no.1
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    • pp.107-113
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    • 1999
  • The purpose of this study was to develop a miniature imaging gamma probe with high performance that can detect small or residual tumors after surgery. Gamma probe detector system consists of NaI(Tl) scintillator, position sensitive photomultiplier tube (PSPMT), and collimator. PSPMT was optically coupled with 6.5 mm thick, 7.62 cm diameter of NaI(Tl) crystal and supplied with -1000V for high voltage. Parallel hexagonal hole collimator was manufactured for characteristics of 40-mm hole length, 1.3-mm hole diameter, and 0.22 mm septal thickness. Electronics consist of position and trigger signal readout systems. Position signals were obtained with summing, subtracting, and dividing circuit using preamplifer and amplifier. Trigger signals were obtained using summing amplifier, constant fraction discriminator, and gate and delay generator module with preamplifer. Data acquisition and processing were performed by Gamma-PF interface board inserted into pentium PC and PIP software. For imaging studies, flood and slit mask images were acquired using a point source. Two hole phantom images were also acquired with collimator. Intrinsic and system spatial resolutions were measured as 3.97 mm and 5.97 mm, respectively. In conclusion, Miniature gamma probe images based on the PSPMT showed good image quality, we conclude that the miniature imaging gamma probe was successfully developed and good image data were obtained. However, further studies will be required to optimize imaging characteristics.

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A Thoracic Spine Segmentation Technique for Automatic Extraction of VHS and Cobb Angle from X-ray Images (X-ray 영상에서 VHS와 콥 각도 자동 추출을 위한 흉추 분할 기법)

  • Ye-Eun, Lee;Seung-Hwa, Han;Dong-Gyu, Lee;Ho-Joon, Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.1
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    • pp.51-58
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    • 2023
  • In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

Serum exosomal miR-192 serves as a potential detective biomarker for early pregnancy screening in sows

  • Ruonan Gao;Qingchun Li;Meiyu Qiu;Su Xie;Xiaomei Sun;Tao Huang
    • Animal Bioscience
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    • v.36 no.9
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    • pp.1336-1349
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    • 2023
  • Objective: The study was conducted to screen differentially expressed miRNAs in sows at early pregnancy by high-throughput sequencing and explore its mechanism of action on embryo implantation. Methods: The blood serum of pregnant and non-pregnant Landrace×Yorkshire sows were collected 14 days after artificial insemination, and exosomal miRNAs were purified for high throughput miRNA sequencing. The expression patterns of 10 differentially expressed (DE) miRNAs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The qRT-PCR quantified the abundance of serum exosomal miR-192 in pregnant and control sows, and the diagnostic power was assessed by receiver operating characteristic (ROC) analysis. The target genes of DE miRNAs were predicted with bioinformatics software, and the functional and pathway enrichment analysis was performed on gene ontology and the Kyoto encyclopedia of genes and genomes terms. Furthermore, a luciferase reporter system was used to identify the target relation between miR-192 and integrin alpha 4 (ITGA4), a gene influencing embryo implantation in pigs. Finally, the expression levels of miRNAs and the target gene ITGA4 were analyzed by qRT-PCR, and western blot, with the proliferation of BeWo cells detected by cell counting kit-8 (CCK-8). Results: A total of 221 known miRNAs were detected in the libraries of the pregnant and non-pregnant sows, of which 55 were up-regulated and 67 were down-regulated in the pregnant individuals compared with the non-pregnant controls. From these, the expression patterns of 10 DE miRNAs were validated. The qRT-PCR analysis further confirmed a significantly higher expression of miR-192 in the serum exosomes extracted from pregnant sows, when compared to controls. The ROC analysis revealed that miR-192 provided excellent diagnostic accuracy for pregnancy (area under the ROC curve [AUC]=0.843; p>0.001). The dual-luciferase reporter assay indicated that miR-192 directly targeted ITGA4. The protein expression of ITGA4 was reduced in cells that overexpressed miR-192. Overexpression of miR-192 resulted in the decreased proliferation of BeWo cells and regulated the expression of cell cycle-related genes. Conclusion: Serum exosomal miR-192 could serve as a potential biomarker for early pregnancy in pigs. miR-192 targeted ITGA4 gene directly, and miR-192 can regulate cellular proliferation.

Full mouth rehabilitation with fixed prostheses by increased vertical occlusal dimension using 3D printed splint in a patient with excessive tooth wear (과도한 치아 마모 환자의 3D 프린팅 교합안정장치를 이용한 수직 교합 고경 증가를 동반한 고정성 보철물 전악 수복 증례)

  • Se-Young Kim;Soo-Yeon Shin
    • The Journal of Korean Academy of Prosthodontics
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    • v.61 no.3
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    • pp.215-226
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    • 2023
  • Severe wear of the anterior teeth facilitates the loss of anterior guidance, which protects the posterior teeth from wear during excursive movement. Additionally, when treating patients with collapsed occlusion due to multiple tooth loss and tooth wear, it is important to determine the presence of vertical dimension loss through accurate clinical and radiographic examinations and diagnostic wax-up. The patient of this case is a 44-year-old female patient who complained of overall tooth wear and loss of posterior teeth due to bruxism and clenching habits, visited the hospital with the address of restoring masticatory function and improving aesthetic appearance through prosthetic treatment. Through model analysis and diagnostic wax-up, an increase in vertical dimension was determined, and full mouth restoration with fixed prostheses was planned. The degree of adaptation to the vertical dimension was confirmed step by step using an occlusal splint designed with CAD (Computer aided design) software and 3-D (3-Dimensional) printed, and then restored with provisional restoration and after a 4-month adaptation period, the entire dentition was restored with metal ceramic crowns and implants. Through this procedure, satisfactory treatment results were obtained in terms of function and aesthetics.

Gear Fault Diagnosis Based on Residual Patterns of Current and Vibration Data by Collaborative Robot's Motions Using LSTM (LSTM을 이용한 협동 로봇 동작별 전류 및 진동 데이터 잔차 패턴 기반 기어 결함진단)

  • Baek Ji Hoon;Yoo Dong Yeon;Lee Jung Won
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.10
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    • pp.445-454
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    • 2023
  • Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

Estimating Gastrointestinal Transition Location Using CNN-based Gastrointestinal Landmark Classifier (CNN 기반 위장관 랜드마크 분류기를 이용한 위장관 교차점 추정)

  • Jang, Hyeon Woong;Lim, Chang Nam;Park, Ye-Suel;Lee, Gwang Jae;Lee, Jung-Won
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.3
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    • pp.101-108
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    • 2020
  • Since the performance of deep learning techniques has recently been proven in the field of image processing, there are many attempts to perform classification, analysis, and detection of images using such techniques in various fields. Among them, the expectation of medical image analysis software, which can serve as a medical diagnostic assistant, is increasing. In this study, we are attention to the capsule endoscope image, which has a large data set and takes a long time to judge. The purpose of this paper is to distinguish the gastrointestinal landmarks and to estimate the gastrointestinal transition location that are common to all patients in the judging of capsule endoscopy and take a lot of time. To do this, we designed CNN-based Classifier that can identify gastrointestinal landmarks, and used it to estimate the gastrointestinal transition location by filtering the results. Then, we estimate gastrointestinal transition location about seven of eight patients entered the suspected gastrointestinal transition area. In the case of change from the stomach to the small intestine(pylorus), and change from the small intestine to the large intestine(ileocecal valve), we can check all eight patients were found to be in the suspected gastrointestinal transition area. we can found suspected gastrointestinal transition area in the range of 100 frames, and if the reader plays images at 10 frames per second, the gastrointestinal transition could be found in 10 seconds.