• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.829-831
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• 2022

포인트 클라우드 콘텐츠는 움직임이 있는 콘텐츠를 연속된 프레임에 3 차원 위치정보와 대응하는 색상으로 기록한 데이터이다. 강체 포인트 클라우드 데이터를 정합하기 위해서는 고전적인 방법이지만 강력한 ICP 정합 알고리즘을 사용한다. 그러나 국소적인 모션 벡터가 있는 비 강체 포인트 클라우드 콘텐츠는 기존의 ICP 정합 알고리즘을 통해서는 프레임 간 정합이 불가능하다. 본 논문에서는 비 강체 포인트 클라우드 콘텐츠를 지역적 확률 모델을 사용하여 프레임 간 포인트의 쌍을 맺고 개별 포인트 간의 모션벡터를 구해 정합 하는 방법을 제안한다. 정합 대상의 데이터를 2 차원 투영을 하여 구조화시키고 정합 할 데이터를 투영하여 후보군 포인트를 선별한다. 선별된 포인트에서 깊이 값 비교와 좌표 및 색상 유사도를 측정하여 적절한 쌍을 찾아준다. 쌍을 찾은 후 쌍으로 모션 벡터를 더하여 정합을 수행하면 비 강체 포인트 클라우드 콘텐츠 데이터에 대해서도 정합이 가능해진다.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.37-44
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• 2006

To use surveying data obtained from different sensors and different techniques, it is a pre-requite step that register them in a common coordinate system. For this purpose, we developed methodologies to register airborne photos, ALS (Airborne Laser Scanning) data and digital maps. To achieve this, conjugate features from these data should be extracted in advance. In this study, linear features are chosen as conjugate features. Based on such a selection strategy, a simple and robust algorithm is proposed for extracting such features from ALS data. Then, to register them, observation equations are established from similarity measurements of the extracted features and the results was evaluated statistically. The results clearly demonstrate that the proposed algorithms are appropriate to register these data.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.225-229
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• 2016

Cancer registration is an important component of a comprehensive cancer control program, providing timely data and information for research and administrative use. Capture-recapture methods have been used as tools to investigate completeness of cancer registry data. This study aimed to estimate the completeness of lung cancer cases registered in Ardabil Population Based Cancer Registry (APBCR) with a three-source capture-recapture method. Data for all new cases of lung cancer reported by three sources (pathology reports, death certificates, and medical records) to APBCR for 2006 and 2008 were obtained. Duplicate cases shared among the three sources were identified based on similarity of first name, last name and father's names. A log-linear model was used to estimate number of missed cases and to control for dependency among sources. A total of 218 new cases of lung cancer was reported by three sources after removing duplicates. The estimated completeness calculated by log-linear method was 26.4 for 2006 and 27.1 for 2008. The completeness differed according to gender. In men, the completeness was 26.0% for 2006 and 28.1 for 2008. In women, the completeness was 36.5% for 2006 and 46.9 for 2008. In conclusion, none of the three sources can be considered as a reliable source for accurate cancer incidence estimation.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.17-27
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• 2012

Open Market is one of the key factors to accelerate the profit. Usually retailers sell items in several Open Market. One of the challenges for retailers is to assign categories of items with different classification systems. In this research, we propose an item category recommendation method to support appropriate products category registration. Our recommendations are based on semantic relation between existing and any other Open Market categorization. In order to analyze correlations of categories, we use Morpheme analysis, Korean Wiki Dictionary, WordNet and Google Translation API. Our proposed method recommends a category, which is most similar to a guide word by measuring semantic similarity. The experimental results show that, our system improves the system accuracy in term of search category, and retailers can easily select the appropriate categories from our proposed method.

• Information Systems Review
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• v.22 no.1
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• pp.17-31
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• 2020

With the start of the fourth industrial revolution era, technologies of various fields are merged and new types of technologies and products are being developed. In addition, the importance of the registration of intellectual property rights and patent registration to gain market dominance of them is increasing in oversea as well as in domestic. Accordingly, the number of patents to be processed per examiner is increasing every year, so time and cost for prior art research are increasing. Therefore, a number of researches have been carried out to reduce examination time and cost for patent-pending technology. This paper proposes a method to calculate the degree of similarity among patent documents of the same priority claim when a plurality of patent rights priority claims are filed and to provide them to the examiner and the patent applicant. To this end, we preprocessed the data of the existing irregular patent documents, used Word2vec to obtain similarity between patent documents, and then proposed recommendation model that recommends a similar patent document in descending order of score. This makes it possible to promptly refer to the examination history of patent documents judged to be similar at the time of examination by the examiner, thereby reducing the burden of work and enabling efficient search in the applicant's prior art research. We expect it will contribute greatly.

• Annals of Surgical Treatment and Research
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• v.95 no.6
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• pp.297-302
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• 2018

Purpose: Increased robotic surgery is attended by increased reports of complications, largely due to limited operative view and lack of tactile sense. These kinds of obstacles, which seldom occur in open surgery, are challenging for beginner surgeons. To enhance robotic surgery safety, we created an augmented reality (AR) model of the organs around the thyroid glands, and tested the AR model applicability in robotic thyroidectomy. Methods: We created AR images of the thyroid gland, common carotid arteries, trachea, and esophagus using preoperative CT images of a thyroid carcinoma patient. For a preliminary test, we overlaid the AR images on a 3-dimensional printed model at five different angles and evaluated its accuracy using Dice similarity coefficient. We then overlaid the AR images on the real-time operative images during robotic thyroidectomy. Results: The Dice similarity coefficients ranged from 0.984 to 0.9908, and the mean of the five different angles was 0.987. During the entire process of robotic thyroidectomy, the AR images were successfully overlaid on the real-time operative images using manual registration. Conclusion: We successfully demonstrated the use of AR on the operative field during robotic thyroidectomy. Although there are currently limitations, the use of AR in robotic surgery will become more practical as the technology advances and may contribute to the enhancement of surgical safety.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.99-105
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• 2015

The growth of internet infrastructure and a tremendous increment of internet users lead actively to found internet newspaper publishing companies, which are able to dig up and publish own news articles. In disregard of these quantitative growth of internet newspaper companies, the qualitative growth of them doesn't coincide with the quantitative growth. Therefore, to require social responsibility and to build healthy media environment, Korean government has put in force registration system of internet newspaper company. According to this system, internet newspaper companies have to produce at the inside over 30 percent of weekly publications, and this requisite increases the needs of its verification. This paper investigates technologies to measure the self-supplied news volumes of internet newspaper company, examines validity of them, and presents appropriate method to measure. To compare huge amount of news articles rapidly, the presented method is based on the modified edit-distance, which reflects human cognition of word and empirical information related with it. To prove correctness of our presented method, we show experimental results for some real internet news articles.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.32-37
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• 2014

The panorama is a good alternative to overcome narrow FOV under study in robot vision, stereo camera and panorama image registration and modeling. The panorama can materialize view with angles wider than human view and provide realistic space which make feeling of being on the scene based on realism. If we use all correspondence, it is too difficult to find strong features and correspondences and assume accurate homography matrix in geographic changes in images as load of calculation increases. Accordingly, we used SURF algorithm to estimate overlapping areas with high similarity by comparing and analyzing the input images' histograms and to detect features. And we solved the problem of input order so we can make panorama by input images without order.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.276-282
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• 2018

Objectives: Due to the uncontrolled increase of the mobile health applications and their scarce use by elderly for reason of absence credibility of measurements by lack scientific support, the aim of this study was to evaluate the differences between the biophysical measurements based on standard instrument against a mobile application using controlled experiments with elderly to propose an effective validation model of the developed apps. Methods: The subjects of the study (50 people) were elderly people who wanted to check their weight and cardiac status. For this purpose, two mobile applications were used to measure energy expenditure based on physical activity (Activ) and heart rate (SMCa) during controlled walking at specific speeds. Minute-by-minute measurements were recorded to evaluate the average error and the accuracy of the data acquired through confidence intervals by means of statistical analysis of the data. Results: The experimental results obtained by the Activ/SMCa apps showed a consistent statistical similarity with those obtained by specialized equipment with confidence intervals of 95%. All the subjects were advised and trained on the use of the applications, and the initial registration of data to characterize them served to significantly affect the perceived ease of use. Conclusions: This is the first model to validate a health-app with elderly people allowed to demonstrate the anthropometric and body movement differences of subjects with equal body mass index (BMI) but younger. Future studies should consider not only BMI data but also other variables, such as age and usability perception factors.

• Progress in Medical Physics
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• v.32 no.4
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• pp.172-178
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• 2021

Purpose: This study aimed to develop a deep learning architecture combining two task models to generate synthetic computed tomography (sCT) images from low-tesla magnetic resonance (MR) images to improve metallic marker visibility. Methods: Twenty-three patients with cervical cancer treated with intracavitary radiotherapy (ICR) were retrospectively enrolled, and images were acquired using both a computed tomography (CT) scanner and a low-tesla MR machine. The CT images were aligned to the corresponding MR images using a deformable registration, and the metallic dummy source markers were delineated using threshold-based segmentation followed by manual modification. The deformed CT (dCT), MR, and segmentation mask pairs were used for training and testing. The sCT generation model has a cascaded three-dimensional (3D) U-Net-based architecture that converts MR images to CT images and segments the metallic marker. The performance of the model was evaluated with intensity-based comparison metrics. Results: The proposed model with segmentation loss outperformed the 3D U-Net in terms of errors between the sCT and dCT. The structural similarity score difference was not significant. Conclusions: Our study shows the two-task-based deep learning models for generating the sCT images using low-tesla MR images for 3D ICR. This approach will be useful to the MR-only workflow in high-dose-rate brachytherapy.