• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.29-38
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• 2018

In this paper, we propose an automatic segmentation method of meniscus in knee MR images by automatic meniscus localization, multi-atlas-based locally-weighted voting, and patch-based edge feature classification. First, after segmenting the bone and knee articular cartilage, the volume of interest of the meniscus is automatically localized. Second, the meniscus is segmented by multi-atlas-based locally-weighted voting taking into account the weights of shape and intensity distribution in the volume of interest of the meniscus. Finally, to remove leakage to the collateral ligaments with similar intensity, meniscus is refined using patch-based edge feature classification considering shape and distance weights. Dice similarity coefficient between proposed method and manual segmentation were 80.13% of medial meniscus and 80.81 % for lateral meniscus, and showed better results of 7.25% for medial meniscus and 1.31% for lateral meniscus compared to the multi-atlas-based locally-weighted voting.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.225-237
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• 2024

In the analysis of competing risks data, some of covariates may not be fully observed for some subjects. In such cases, excluding subjects with missing covariate values from the analysis may result in biased estimates and loss of efficiency. In this paper, we studied multiple imputation and the augmented inverse probability weighting method for regression parameter estimation in the cause-specific proportional hazards model with missing covariates. The performance of estimators obtained from multiple imputation and the augmented inverse probability weighting method is evaluated by simulation studies, which show that those methods perform well. Multiple imputation and the augmented inverse probability weighting method were applied to investigate significant risk factors for the risk of death from breast cancer and from other causes for breast cancer data with missing values for tumor size obtained from the Prostate, Lung, Colorectal, and Ovarian Cancer Screen Trial Study. Under the cause-specific proportional hazards model, the methods show that race, marital status, stage, grade, and tumor size are significant risk factors for breast cancer mortality, and stage has the greatest effect on increasing the risk of breast cancer death. Age at diagnosis and tumor size have significant effects on increasing the risk of other-cause death.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.697-712
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• 2013

When analyzing repeated binary data, the generalized estimating equations(GEE) approach produces consistent estimates for regression parameters even if an incorrect working correlation matrix is used. However, time-varying covariates experience larger changes in coefficients than time-invariant covariates across various working correlation structures for finite samples. In addition, the GEE approach may give biased estimates under missing at random(MAR). Weighted estimating equations and multiple imputation methods have been proposed to reduce biases in parameter estimates under MAR. This article studies if the two methods produce robust estimates across various working correlation structures for longitudinal binary data with time-varying covariates under different missing mechanisms. Through simulation, we observe that time-varying covariates have greater differences in parameter estimates across different working correlation structures than time-invariant covariates. The multiple imputation method produces more robust estimates under any working correlation structure and smaller biases compared to the other two methods.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.381-388
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• 2015

TCP, which performs congestion control in congestion condition, is able to help a reliable transmission. However, packet loss can be increased because congestion window is increased by the time the packet is dropped in the process of congestion avoidance. In this paper, to solve the above problem, we propose a new congestion estimation based TCP congestion control scheme using the weighted average value of the RTT. After measuring a SRTT, which means the weighted average value of RTTs, at this point of time when a buffer overflow is occurred by an overloaded packet, the proposed scheme estimates the time, when the same SRTT is made in packet transmission, as a congestion time and then decreases the congestion window. The simulation results show that the proposed schem has a good performance in terms of packet loss rate and throughput when the packet loss due to buffer overflow is larger than that due to wireless channel.

• The Korean Journal of Applied Statistics
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• v.9 no.1
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• pp.91-109
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• 1996

Exponentially weighted moving averae(EWMA) control chart has been used widely for process monitoring and process adjustment recently, but there has not been many studies about the selection of the parameters. Design of the control chart can be classified into the statistical design and the economic design. The purpose of the economic design is to minimize the cost function in which all the possible costs occurring during the process are probability given the Type I error probability. In this paper the optimal parameters of the EWMA chart are selected for the economic design as well as for the statistical design. The optimal parameters for the economic design show significantly different from those of the statistical design, and especially the weight is always larger than that used in the statistical design. In the economic design, we divide the model into the single assignable cause model and the multiple assignable causes model caacording to number of which is used as the average context of the multiple assignable causes, it shows that the selection of the parameters may be misleading when the multiple assignable causes exist in practice.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.653-655
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• 1999

카메라 영상을 통하여 무인 헬리콥터 동작을 추정하기 위해 적응형 가중치를 사용한 새로운 Ego-Motion을 검출 기법을 제안하였다. 무인 헬리콥터 동적 특성은 비선형이며, 심한 진동 발생으로 영상 번짐(blur) 현상이 나타나기 때문에 상관 값만을 고려한 정합 방법으로는 빈번히 오차가 발생한다. 본 논문에서는 가속도, 각 가속도 및 제어입력 값에 의한 위치 추정 값과 상관 값 및 에지 강도를 가중치에 의해 융합하여 정확한 Ego-Motion을 계산할 수 있는 기법을 제안하였다. 또한 무인 헬리콥터의 가속도, 각 가속도, 상하 속도에 따라서 영상의 번짐 정도가 달라 이들 같이 크면 위치오차에 가중을 크게 주고, 작으면 상관 값에 가중치를 적게 주는 적응형 가중치 결정 알고리즘을 적용하였다. 제안한 적응형 가중치 기법을 무인 헬리콥터에 실험한 결과 카메라에 포착된 영상에 의해 무인헬기의 동작을 정확히 추정 할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.649-652
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• 2006

폐나, 기관지 등의 호흡기, 기타 장기에는 매우 미세한 크기의 털 형태의 섬모라고 하는 부속기관을 가지고 있다. 점액을 이동시키고 기타 물질들을 배출할 때 유용한 역할을 하는 이 섬모들은 동기화된 패턴으로 진동을 한다. 이러한 움직임은 각각의 종이 가진 특성뿐만 아니라, 같은 종의 현재의 상태에 따라 다양한 특징들을 보여준다. 시약 투여 시 혹은 환경 변화에 따른 생체 반응 등과 같이 다양한 특성 및 반응 연구에 이러한 섬모의 진동 주파수 (Ciliary Beat Frequency, CBF)를 이용하고 있다. 섬모의 진동 주파수 측정에 대해 몇몇 연구가 있어왔으나, 규격화되거나 대표적인 방법은 아직까지 없으며, 각각의 방법마다 잡음에 약하든지, 빠르게 움직이는 섬모의 주파수 측정에 어려움이 있거나, 고비용 시스템 필요 등의 단점들이 있다. 최근 들어 영상 기술의 발달로 영상을 이용한 CBF 측정 방법들이 제안되고 있다. 본 논문에서는 CCD 카메라로 촬영한 영상을 이용해서 섬모의 영상에서 가중 평균을 응용한 위치 값으로 섬모의 움직임을 추출, FFT를 통해 보다 정확하고 간편하며 좀 더 다양한 영상에 적용시킬 수 있는 CBF 측정 방법을 제시한다.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.215-221
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• 2001

In this paper, we propose a algorithm that apply different weight-sampling values according to the directions of the contour to reduce errors that can arise in extracting the feature of an contoured object. Especially, it 8is designed to have invariant property under the circumstances like the rotation, transition and scaling. The output matrix of feature set is made through the size function of the proposed algorithm, and the euclidean distance between the output matrix and that of the original image is calculated. Experimental result shows that the proposed algorithm reduces the euclidean distance between the original image and the changed image-by 57% in rotation and by 91% in scaling.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.128-132
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• 1996

In [1], it is shown that a subclass of ETBFs, which are self-dual ETBFs, can be expressed as a weighted average of median subfiltered outputs. In this paper, we extend this result to general ETBFs. In particular, we show that any ETBF can be represented as a weighted average of minimum (or maximum) subfiltered outputs. These representations naturally lead to a subclass of ETBF, called the K-th order ETBF (K-ETBF) that employs only those subfilters whose window sizes are less than or equal to K. By designing K-ETBFs under the mean square error criterion for various values of K and applying them to restore noisy signals, the tradeoff between the performance and the complexity of this class of filters is examined.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.89-96
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• 2009

In this paper, we propose an efficient deinterlacing algorithm which is an edge dependent interpolation based on edge direction refinement. The conventional edge dependent interpolation algorithms have a visually better performance than any other Intra-field deinterlacing algorithms. However they are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method detects edge direction of around interpolated pixel and refines the edge direction using weighted median filter. Simulation results have shown the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.