• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.18-23
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• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• Journal of Biomedical Engineering Research
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• v.36 no.2
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• pp.43-47
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• 2015

Osteoarthritis is the most common chronic joint disease in the world. With its progression, cartilage thickness tends to diminish, which causes severe pain to human being. One way to examine the stage of osteoarthritis is to measure the cartilage thickness. When it comes to inter-subject study, however, it is not easy task to compare cartilage thickness since every human being has different cartilage structure. In this paper, we propose a method to assess cartilage defect using MRI inter-subject thickness comparison. First, we used manual segmentation method to build accurate atlas images and each segmented image was labeled as articular surface and bone-cartilage interface in order to measure the thickness. Secondly, each point in the bone-cartilage interface was assigned the measured thickness so that the thickness does not change after registration. We used affine transformation and SyGN to get deformation fields which were then applied to thickness images to have cartilage thickness atlas. In this way, it is possible to investigate pixel-by-pixel thickness comparison. Lastly, the atlas images were made according to their osteoarthritis grade which indicates the degree of its progression. The result atlas images were compared using the analysis of variance in order to verify the validity of our method. The result shows that a significant difference is existed among them with p < 0.001.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.996-1008
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• 2009

This paper proposes a novel approach for the model-based pose matching of a human body using Active Shape Models. To improve the processing time of model creation and registration, we use a skeleton-type model instead of the conventional silhouette-based models. The skeleton model defines feature information that is used to match the human pose. Images used to make the model are for 600 human bodies, and the model has 17 landmarks which indicate the body junction and key features of a human pose. When applying primary Active Shape Models to the skeleton-type model in the matching process, a problem may occur in the proximal joints of the arm and leg due to the color variations on a human body and the insufficient information for the fore-rear directions of profile normals. This problem is solved by using the background subtraction information of a body region in the input image and adding a 4-directions feature of the profile normal in the proximal parts of the arm and leg. In the matching process, the maximum iteration is less than 30 times. As a result, the execution time is quite fast, and was observed to be less than 0.03 sec in an experiment.

• Journal of Korea Game Society
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• v.9 no.1
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• pp.135-142
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• 2009

Nowadays, many interface devices or training systems for the disabled are being developed and introduced with the recent development in IT technology but only few training systems for the developmental disabled are introduced. In this paper, we present a situation training system based on the argumented reality in order to help the developmental disabled to increase their management level of capability to the certain situation. Our system is specifically based on the food serving in the restaurant. This maker-based system provides trainees to safely experience various different situations and take the training session under any circumstances. The trainees for this program are able to look around with the HMD on, take the training easily by following the voice instruction, and try situational scenario.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.430-435
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• 2006

In this paper, we propose a method based on multimodal biometrics system using the face and signature under ubiquitous computing environments. First, the face and signature images are obtained by PDA and then these images with user ID and name are transmitted via WLAN(Wireless LAN) to the server and finally the PDA receives verification result from the server. The multimodal biometrics recognition system consists of two parts. In client part located in PDA, user interface program executes the user registration and verification process. The server consisting of the PCA and LDA algorithm shows excellent face recognition performance and the signature recognition method based on the Kernel PCA and LDA algorithm for signature image projected to vertical and horizontal axes by grid partition method. The proposed algorithm is evaluated with several face and signature images and shows better recognition and verification results than previous unimodal biometrics recognition techniques.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.65-67
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• 2002

A PC based software, the RTP Research Tool Box (RTB), was developed for IMRT optimization research. The software was consisted of an image module, a beam registration module, a dose calculation module, a dose optimization module and a dose display module. The modules and the Graphical User Interface (GUI) were designed to easily amendable by negotiating the speed of performing tasks. Each module can be easily replaced to new functions for research purpose. IDL 5.5 (RSI, USA) language was used for this software. Five major modules enable one to perform the research on the dose calculation, on the dose optimization and on the objective function. The comparison of three cost functions, such as the uncomplicated tumor control probability (UTCP), the physical objective function and the pseudo-biological objective function, which was designed in this study, were performed with the RTB. The optimizations were compared to the simulated annealing and the gradient search optimization technique for all of the optimization objective functions. No significant differences were found among the objective functions with the dose gradient search technique. But the DVH analysis showed that the pseudo-biological objective function is superior to the physical objective function when with the simulated annealing for the optimization.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.345-347
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• 2012

본 논문에서는 4-조각 전립선 병리조직 영상을 기하 보정 및 강체 정합하여 자동 스티칭하는 방법을 제안한다. 4-조각 병리영상에 대하여 총 3번의 스티칭을 수행하는데, 좌, 우 조각영상의 상, 하 영상 간 스티칭을 각각 수행 한 후 좌, 우 조각 영상 간 스티칭을 수행한다. 강체 정합 전 병리 조각의 코너를 이용해 x-축, y-축 방향의 위치보정과 회전보정을 수행하는 기하보정 단계를 거침으로서 지역적 최적해로의 수렴을 방지하며, 강체 정합의 정확성을 높인다. 병리영상은 전체적으로 밝기값이 유사하므로 밝기값이 아닌 외곽선 정보를 이용하여 조각 영상간의 거리를 최소화시켜 강체 정합한다. 실험 결과, 4-조각 전립선 병리조직 영상이 지역적 최적해에 수렴하지 않고, 조각 영상 간 거리를 최소화 하며, 하나로 스티칭 됨을 확인할 수 있었다. 제안 방법의 총 수행 시간은 평균 10.32초로 측정되었다. 본 논문의 제안 방법은 4조각으로 나뉜 전립선 병리조직 영상을 하나로 스티칭 함으로서 해당 조직의 전체 구조 파악 및 조직 내에서의 암의 위치 파악에 사용 될 수 있으며 이를 통한 전립선암의 확진에도 사용 될 수 있다.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.495-506
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• 2011

COMS In-Orbit Tests(IOT), performed from July, 2010 to Jan, 2011, were successfully completed and the scientific data from MI and GOCI has been distributed officially from April, 2011. This paper focuses on the geometric calibration system tests conducted during the IOT. The geometric calibration process, which is one of the primary objectives of the IOT is the final step of COMS data pre-processing. The basic principles of the geometric calibration (or image navigation and registration, INR) algorithm for COMS are described and the functional and performance tests of COMS INR system were summarized according to the COMS IOT phases. Final performance testes were carried out using data sets acquired from the real-time COMS data pre-processing system. Geometric calibration accuracy of the COMS data showed excellent quality and met requirement specifications.

• Radiation Oncology Journal
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• v.36 no.2
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• pp.122-128
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• 2018

Purpose: To investigate positional uncertainty and its correlation with clinical parameters in spine stereotactic body radiotherapy (SBRT) using thermoplastic mask (TM) immobilization. Materials and Methods: A total of 21 patients who underwent spine SBRT for cervical or upper thoracic spinal lesions were retrospectively analyzed. All patients were treated with image guidance using cone beam computed tomography (CBCT) and 4 degrees-of-freedom (DoF) positional correction. Initial, pre-treatment, and post-treatment CBCTs were analyzed. Setup error (SE), pre-treatment residual error (preRE), post-treatment residual error (postRE), intrafraction motion before treatment (IM1), and intrafraction motion during treatment (IM2) were determined from 6 DoF manual rigid registration. Results: The three-dimensional (3D) magnitudes of translational uncertainties (mean ${\pm}$ 2 standard deviation) were $3.7{\pm}3.5mm$ (SE), $0.9{\pm}0.9mm$ (preRE), $1.2{\pm}1.5mm$ (postRE), $1.4{\pm}2.4mm$ (IM1), and $0.9{\pm}1.0mm$ (IM2), and average angular differences were $1.1^{\circ}{\pm}1.2^{\circ}$ (SE), $0.9^{\circ}{\pm}1.1^{\circ}$ (preRE), $0.9^{\circ}{\pm}1.1^{\circ}$ (postRE), $0.6^{\circ}{\pm}0.9^{\circ}$ (IM1), and $0.5^{\circ}{\pm}0.5^{\circ}$ (IM2). The 3D magnitude of SE, preRE, postRE, IM1, and IM2 exceeded 2 mm in 18, 0, 3, 3, and 1 patients, respectively. No association were found between all positional uncertainties and body mass index, pain score, and treatment location (p > 0.05, Mann-Whitney test). There was a tendency of intrafraction motion to increase with overall treatment time; however, the correlation was not statistically significant (p > 0.05, Spearman rank correlation test). Conclusion: In spine SBRT using TM immobilization, CBCT and 4 DoF alignment correction, a minimum residual translational uncertainty was 2 mm. Shortening overall treatment time and 6 DoF positional correction may further reduce positional uncertainties.