• Journal of radiological science and technology
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• v.32 no.1
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• pp.45-52
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• 2009

Digital Mammography is an efficient imaging technique for the detection and diagnosis of breast pathological disorders. Six mammographic criteria such as number of cluster, number, size, extent and morphologic shape of microcalcification, and presence of mass, were reviewed and correlation with pathologic diagnosis were evaluated. It is very important to find breast cancer early when treatment can reduce deaths from breast cancer and breast incision. In screening breast cancer, mammography is typically used to view the internal organization. Clusterig microcalcifications on mammography represent an important feature of breast mass, especially that of intraductal carcinoma. Because microcalcification has high correlation with breast cancer, a cluster of a microcalcification can be very helpful for the clinical doctor to predict breast cancer. For this study, three steps of quantitative evaluation are proposed : DoG filter, adaptive thresholding, Expectation maximization. Through the proposed algorithm, each cluster in the distribution of microcalcification was able to measure the number calcification and length of cluster also can be used to automatically diagnose breast cancer as indicators of the primary diagnosis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.86-96
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• 2000

The representative area among the ones whose cost increases as the integration ratio increases is the test area. As the relative cost of hardware decreases, the BIST method has been focued on as the future-oriented test method. The biggest drawback of it is the increasing test time to obtain the acceptable fault coverage. This paper proposed a BIST implementation method to reduce the test times. This method uses an input grouping and test point insertion method, in which the definition of test point is different from the previous one. That is, the test points are defined on the basis of the internal nodes which are the reference points of the input grouping and are merging points of the grouped signals. The main algorithms in the proposed method were implemented with C-language, and various circuits were used to apply the proposed method for experiment. The results showed that the test time could be reduced to at most $1/2^{40}$ of the pseudo-random pattern case and the fault coverage were also increased compared with the conventional BIST method. The relative hardware overhead of the proposed method to the circuit under test decreases as th e size of the circuit to be tested increases, and the delay overhead by the BIST utility is negligible compared to that of the original circuit. That means, the proposed method can be applied efficiently to large VLSI circuits.

• Progress in Medical Physics
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• v.14 no.3
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• pp.151-160
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• 2003

The application of more complex radiotherapy techniques using multileaf collimation (MLC), such as 3D conformal radiation therapy and intensity-modulated radiation therapy (IMRT), has increased the significance of verifying leaf position and motion. Due to thier reliability and empirical robustness, quality assurance (QA) of MLC. However easy use and the ability to provide digital data of electronic portal imaging devices (EPIDs) have attracted attention to portal films as an alternatives to films for routine qualify assurance, despite concerns about their clinical feasibility, efficacy, and the cost to benefit ratio. In this study, we developed method for daily QA of MLC using electronic portal images (EPIs). EPID availability for routine QA was verified by comparing of the portal films, which were simultaneously obtained when radiation was delivered and known prescription input to MLC controller. Specially designed two-test patterns of dynamic MLC were applied for image acquisition. Quantitative off-line analysis using an edge detection algorithm enhanced the verification procedure as well as on-line qualitative visual assessment. In conclusion, the availability of EPI was enough for daily QA of MLC leaf position with the accuracy of portal films.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.69-76
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• 2006

TRISO(tri-isotropic)-coated fuel particle technology is utilized owing to its higher stability at a high temperature and Its efficient retention capability for fission products In the HTGR(high temperature gas-reeled reactor). The typical spherical TRISO fuel panicle with a diameter of about 1mm is composed of a nuclear fuel kernel and outer coating layers. The outer coating layers consist of a buffer PyC(pyrolytic carbon) layer, Inner PyC(1-PyC) layer, SiC layer, and outer PyC(O-PyC) layer Most of the Inspection Items for the TRTSO-coated fuel particle depend on destructive methods. The coating thickness of the TRISO fuel particle can be nondestructively measured by the X-ray radiography without generating radioactive wastel. In this study, the coaling thickness for the simulated TRISO-coated fuel particle with $ZrO_2$ kernel Instead of $%UO_2$ kernel was measured by using micro-focus X-ray radiography with micro-focus X-ray generator and flat panel detector The radiographic image was also enhanced by image processing technique to acquire clear boundary lines between coating layers. The coaling thickness wat effectively measured by applying the micro-focus X-ray radiography The inspection process for the TRISO-coated fuel particles will be improved by the developed micro-focus X-ray radiography and digital image processing technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2460-2470
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• 2009

In this study, the parameter extraction for evaluation of the anesthesia depth in each anesthesia stages was conducted. An object of the this experiment study has studied 5 adult patients (mean $\pm$ SD age:$42{\pm}9.13$), ASA classification I and II, undergoing surgery of obstetrics and gynecology. Anaesthesia was maintained with Enflurane. HRV signal was created by R-peak detection algorithm form ECG signal. The HRV data were preprocessing algorithm. It has tried find out the anesthesia parameter which responds the anesthesia events and shows objective anesthesia depth according to anesthesia stage including pre-anesthesia, induction, maintenance, awake and post-anesthesia. In this study, proposed algorithm to analysis the HRV(heart rate variability) signal using wavelet transform in anesthesia stage. Three sorts of wavelet functions applied to PSD. In the result, all of the results were showed similarly. But experiment results of Daubeches 10 is better. Therefore, this parameter is the best parameter in the evaluation of anesthesia stage.