• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.201-206
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• 2003

In clinical practice, CT Angiography is a powerful technique for the visualziation of blood flow in arterial vessels throughout the body. However CT Angiography images of blood vessels anywhere in the body may be fuzzy if the patient moves during the exam. In this paper, we propose a novel technique for removing global motion artifacts in the 3D space. The proposed methods are based on the two key ideas as follows. First, the method involves the extraction of a set of feature points by using a 3D edge detection technique based on image gradient of the mask volume where enhanced vessels cannot be expected to appear, Second, the corresponding set of feature points in the contrast volume are determined by correlation-based registration. The proposed method has been successfully applied to pre- and post-contrast CTA brain dataset. Since the registration for motion correction estimates correlation between feature points extracted from skull area in mask and contrast volume, it offers an accelerated technique to accurately visualize blood vessels of the brain.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.512-516
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• 2008

복수의 영상들 간에 존재하는 변형을 빠른 속도로 파악할 수 있는 영상 등록 방법을 제안한다. 제안하는 방법은 문자인식 및 얼굴인식 분야에서 많이 사용되는 N-tuple 방법을 영상 등록에 적용함으로써 영상간 회전 및 이동 상태를 고속으로 파악한다. 또한 특정 특징을 이용하지 않아 영상의 종류에 무관하게 적용할 수 있으며 소수점 화소 단위의 변형도 파악할 수 있다. 실험을 통해 영상 패치를 이용한 영상 등록 방법과 속도 및 정확도를 비교한 결과, 제안하는 방법이 속도와 정확도 면에서 우수함을 보였다.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1454-1464
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• 2013

In this paper, we propose a rapid rigid registration method for the fusion visualization of intra-operative 2D XA and pre-operative 3D CTA images. In this paper, we propose a global movement estimation based on a trilateration for the fast and robust initial registration. In addition, the principal axis of each image is generated and aligned, and the bounding box of the vascular shape is compared for more accurate initial registration. For the fine registration, two images are registered where the distance between two vascular structures is minimized by selective distance measure. In the experiment, we evaluate a speed, accuracy and robustness using five patients' data by comparing the previous registration method. Our proposed method shows that two volumes can be registered at optimal location rapidly, and robustly comparing with the previous method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.8
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• pp.164-170
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• 2004

The skin movement artifacts are referred to as the relative motion of skin with respect to the motion of underlying bones. This is of great importance in joint biomechanics or internal kinematics of human body. This paper describes a novel experiment that measures the skin movement of a hand based on MR(magnetic resonance) images in conjunction with surface modeling techniques. The proposed approach consists of 3 phases: (1) MR scanning of a hand with surface makers, (2) 3D reconstruction from the MR images, and (3) registration of the 3D models. The MR images of the hand are captured by 3 different postures. And the surface makers which are attached to the skin are employed to trace the skin motion. After reconstruction of 3D models from the scanned MR images, the global registration is applied to the 3D models based on the particular bone shape of different postures. The results of registration are then used to trace the skin movement by measuring the positions of the surface markers.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.683-686
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• 2005

This study addresses a photogrammetric approach to generate Mars topographic products from mapping data of Mars Global Surveyor (MGS). High-resolution stereo images and laser altimetry data collected from the MGS mission are combined and processed to produce Digital Elevation Models (DEM) and orthoimages. First, altimeter data is registered to high resolution images and considerable registration offset (around 325 m) is discovered on high resolution stereo images. Altimetry data, exterior orientation elements of the camera and conjugate points are used for bundle adjustment to solve this mis-registration and detennine the ground coordinates. The mis-registration of altimetry data are effectively eliminated after the bundle adjustment. Using the adjusted exterior orientation the ground coordinates of conjugate points are detennined. A sufficient number of corresponding points collected through image matching and their precise 3-D ground coordinates are used to generate DEM and orthoimages. A posteriori standard deviations of ground points after bundle adjustment indicate the accuracy of OEM generated in this study. This paper addresses the photogrammetric procedure: the registration of altimetry data to stereo pair images, the bundle adjustment and the evaluation, and the generation of OEM and orthoimages.

• Smart Structures and Systems
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• v.25 no.5
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• pp.631-641
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• 2020

To meet the urgent requirements of safety surveillance from civil engineering management authorities, this study proposes a refined and efficient approach to generate full-field high-resolution panorama of construction sites using camera-amounted UAV (Unmanned Aerial Vehicle). GPS (Global Position System) information extraction for pre-registration, feature points filtering for efficient registration and optimal seaming line seeking for fusion are performed in sequence to form the full-field panorama generation framework. Advantages of the proposed method are as follows. First, GPS information can sort images for pre-registration, avoiding inefficient repeated pairwise calculations and matching. Second, the feature points are filtered according to the characteristics of the construction site images to reduce the amount of calculation. The proposed framework is validated on a road construction site and results demonstrate that it can generate an accurate and high-quality full-site panorama for the safety supervision in a much efficient manner.

• Journal of Distribution Science
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• v.14 no.4
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• pp.5-11
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• 2016

Purpose - The Education Ministry has plans to select top 10 percent academic journals among the domestic registration journals in NRF(National Research Foundation of Korea), and designate them as outstanding academic journals. To reflect this trend, KODISA has set its sights on paper publication rate and citation index with pushing forward globalism. First, this study will arrange the process of globalism and the current state of paper submission, and propose the direction of improvement in academic journals through understanding the characteristics of each major field. Research design, data, and methodology - KODISA has preceeded in examining and publishing research papers related to distribution field through indirectly or stimulating academic advancement. KODISA covers the whole fields in social science as well as in business administration and economics that associated with distribution field not limiting only within the range of distribution field. That is, the new subject that contributes to the progress in distribution field with original research can be a priority criteria in KODISA journal publication. Results - The major fields in papers published in KODISA can be categorized broadly as distribution field with economic and business administration point of view. Therefore, the distribution field with economic point of view includes the issues such as regulations, system, industry, market environment, distribution system, trade, and macroeconomics, etc. The business administration point of view in distribution includes distribution strategy, distribution organization, and distribution channel from the perspectives of the firm, etc. Conclusions - The aim of KODISA in 2020 is to be a global academic journal as SCI level of each journal in KODISA, JDS(Registration journal), IJIDB(Registration candidate), EAJBM(Registration candidate), JAFEB(Cabell's Registration journal). The KODISA journals have already settled as the largest academic society and journals of Korea in 2016 currently from humanities and social sciences area by the most gross in publication circulation, volumes, and types. Hereafter, KODISA will focus on the improvement for the objective indicators such as Impact Factor and Centrality index as qualitative growth as well as quantitative expansion. By doing so, KODISA will be a forum for developmental academic debate with attracting the world's greatest scholars' papers. Furthermore, they will be recognized journals and grow as the first-rate academic journals inside and outside of Korea.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Journal of Preventive Medicine and Public Health
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• v.41 no.2
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• pp.84-91
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• 2008

The World Health Organization (WHO) reported that cancer killed 7.6 million people in the world in 2005, and that 40% of all cancer deaths can be prevented. According to the WHO Global Action Plan Against Cancer (GAPAC), monitoring of cancer patients is the essential part of cancer control, and should be conducted through cancer registration. Originally, cancer registries were primarily concerned with the description of cancer patterns, trends of cancer occurrence, and etiology of cancer. In the last 20 years, cancer registries provided not only information on the incidence and characteristics of specific cancers, but also supplied the source of cancer control planning and evaluation and the care of individual cancer patients with survival. Cancer Incidence in Five Continents (CI5) presents incidence data from populations all over the world every five year. Volume IX in the series (data for 1998-2002) has recently (November 2007) been published online at International Agency for Research on Cancer (IARC). Nine data from Korea Central Cancer Registry (National data), Seoul, Busan, Daegu, Gwangju, Incheon, Daejeon, Usan, Jejudo regional cancer registries were included in that volume. In this paper, the editorial process, the characteristics of national data, and quality indices in CI5 IX are being described. In addition, cancer control activities related to cancer registration in some selected countries are also presented.