• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.173-181
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• 2014

In this paper, the algorithm that can automatically segment the lung, the airway and the pulmonary vessels in a chest CT was proposed. The proposed method is progressed in three steps. In the first step, the lung and the airway are segmented by the region growing law through the optimal threshold and three-dimensional labeling. In the second, from the start point to the first carina of the airway is segmented by the deduction operation, and the next airway of the bifurcations are segmented by applying a variable threshold technique. In the third step, the left/right lungs are divided by the restoration process for the lung, and the outside of lungs for abnormal is checked by applying the advanced rolling ball algorithm, and if abnormal is found, that part is removed, and it is restored to the normal lungs by connecting the outside of the lung in the form of second-order polynomial. Finally, pulmonary vessels are segmented by applying the three-dimensional connected component labeling method and three-dimensional region growing method. As the results of simulation, it could be confirmed that the pulmonary vascular is accurately divided without loss of tissue around lung.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1698-1705
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• 2010

In this paper, we propose a fast liver segmentation method from magnetic resonance(MR) images. Our method efficiently divides a MR image into a set of discrete objects, and boundaries based on the normalized gradient magnitude information. Then, the objects belonging to the liver are detected by using 2D seeded region growing with seed points, which are extracted from the segmented liver region of the slice immediately above or below the current slice. Finally, rolling ball algorithm, and connected component analysis minimizes false positive error near the liver boundaries. Our method was validated by twenty data sets and the results were compared with the manually segmented result. The average volumetric overlap error was 5.2%, and average absolute volumetric measurement error was 1.9%. The average processing time for segmenting one data set was about three seconds. Our method could be used for computer-aided liver diagnosis, which requires a fast and accurate segmentation of liver.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1146-1152
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• 2003

Satellite television receiving antenna is required for watching TV on the vehicles, ship and car. Recently TV is not only facility as getting information but one of utility in our life. In Korea, already on the service multi-channel satellite TV using excellent visibility and sound, and there are many users using now by fixing antenna. On this thesis, developed ship's satellite TV receiving antenna, the azimuth controlling is adopted azimuth information using gyro sensor and differential of receiving signal strength algorithm, and elevation controlling used gimbals. The result of this research is successfully implemented Korean satellite tracking antenna as performance until ${\pm}$30 degree roll and pitch of ship motion.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.19-26
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• 2018

We proposed a numerical calculation of the proportion of necrotic cells in pulmonary segmentation, pulmonary vessel segmentation lung disease site for diagnosis of lung disease from chest CT images. The first step is to separate the lungs and bronchi by applying a three-dimensional labeling technique from a chest CT image and a three-dimensional region growing method. The second step is to divide the pulmonary vessels by applying the rate of change using the first order polynomial regression, perform noise reduction, and divide the final pulmonary vessels. The third step is to find a disease prediction factor in a two-step image and calculate the proportion of necrotic cells.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2907-2915
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• 2018

Journal of the Korean Data Analysis Society founded in 1998 has played the role of a major application journal. In this study, we checked the objective of this journal by checking the abstracts for 10 years. Abstract data was crawled from the online journal site (kdas.jems.or.kr) and analyzed by topic model. As a result, we found 18 topics from 2680 abstracts that had several contents, for example, nursing, marketing, economics, regression, factor analysis, data mining and statistical inferences. Topic1 (regression) is most frequent with 460 documents and we found the usefulness of regression in the applied science area. We confirmed the significant 10 association rules using by Fisher's exact test. Also, for exploring the trend of topics, we conducted the topic analysis for two periods which are 2006-2011 period and 2012-2016 period. We found that the control study was more frequent than survey study over time and regression and factor analysis were frequent regardless of time.