• Journal of KIISE:Software and Applications
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• v.33 no.3
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• pp.335-343
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• 2006

This paper proposes a novel technique of marker-based 2D-3D registration to combine 3D information obtained from preoperative CT images into 2D image obtained from intraoperative x-ray fluoroscopy image. Our method is divided into preoperative and intraoperative procedures. In preoperative procedure, we generate CT-derived DRRs using graphics hardware and detect markers automatically. In intraoperative procedure, we propose a hierarchical two- step registration to reduce a degree of freedom from 6-DOP to 2-DOF which is composed of in-plane registration using principal axis method and out-plane registration using minimal error searching method in spherical coordinate. For experimentation, we use cardiac phantom datasets with confirmation markers and evaluate our method in the aspects of visual inspection, accuracy and processing time. As experimental results, our method keeps accuracy and aligns very fast by reducing real-time computations.

• The Journal of the Korea Contents Association
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• v.3 no.3
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• pp.85-97
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• 2003

Medical tomography images like CT, MRI, PET, SPECT, fMRI, ett have been widely used for diagnosis and treatment of a patient and for clinical study in hospital. In many cases, tomography images are scanned in several different modalities or with time intervals for a single subject for extracting complementary information and comparing one another. 3D image registration is mapping two sets of images for comparison onto common 3D coordinate space, and may be categorized to marker -based matching and feature-based matching. 3D registration of brain images has an important role for visual and quantitative analysis in localization of treatment area of a brain, brain functional research, brain mapping research, and so on. In this article, marker-based and feature-based matching methods which are often used are introduced.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.392-401
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• 2006

Image Guided Surgery (IGS) system which has variously tried in medical engineering fields is able to give a surgeon objective information of operation process like decision making and surgical planning. This information is displayed through 3D images which are acquired from image modalities like CT and MRI for pre-operation. The technique of image registration is necessary to construct IGS system. Image registration means that 3D model and the object operated by a surgeon are matched on the common frame. Major techniques of registration in IGS system have been used by recognizing fiducial markers placed on the object. However, this method has been criticized due to additional trauma, its invasive protocol inserting fiducial markers in patient's bone and generating noise data when 2D slice images are acquired by image modality because many markers are made of metal. Therefore, this paper developed shape-based registration technique to improve the limitation of fiducial marker based IGS system. Iterative Closest Points (ICP) algorithm was used to match corresponding points and quaternion based rotation and translation transformation using closed form solution applied to find the optimized cost function of transformation. we assumed that this algorithm were used in Total Knee replacement (TKR) operation. Accordingly, we have developed region-based 3D registration technique based on anatomical landmarks and this registration algorithm was evaluated in a femur model. It was found that region-based algorithm can improve the accuracy in 3D registration.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.20-30
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• 2012

The biggest advantage of AR is that it allows unique experience in the real world through a virtual object. However, there is a limit in the marker techniques to do registration for the virtual object. Therefore, it is possible for a complication that only allows restrictive interaction to come up. This paper provides marker technique of the next generation which can supplement limitations of existing marker technique. Such marker is a combination of IR LED's, and is a convergence of LED VCL concepts of M2M. Environment where the user belongs to and their unique choice will be expressed into one context. Also, the context will be delivered to the system through OOK IR LED marker algorithm. Marker can be operated on the spot to change virtual objects according to the user's taste, registration can be done at the same time for several virtual objects, and control become possible.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.1-9
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• 2009

Using the projected 2-dimensional tilted images obtained from the transmission electron microscopy, we can reconstruct the 3-dimensional structures of objects, such as cells. As a preprocessing procedure, the tilted images should be registered and compensated in terms of the spatial position and the intensity difference, respectively. In this paper, we employ the fiducial marker-based approach to perform a registration, and introduce a simple intensity compensation scheme. Based on the transmissivity image formation model, we propose an algorithm that can compensate the components of the illumination and transmissivity of each image according to the tilted angle. Numerical analysis using real images obtained from the transmission electron microscopy are shown in this paper to show the performance of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.71-81
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• 2012

In order to support simple authoring an application of augmented reality for diverse users, the process for the object registration comprised of tracking and recognizing the object should be accomplished intuitively and simple. Although many 3D reconstruction methods to be applied to the object registration have been developed, the methods have not beyond the experimental level yet. In this paper, we proposed a novel marker-based tangible interfaces for various users to manipulate the object with intuitive and simple approaches during an authoring applications fo augmented reality. The proposed method make use of marker as intuitive interface to obtain 3D geometric information of 3D reconstruction. 3D geometric information of an object surface is acquired by touching the object directly with the proposed tangible interfaces. The tangible interfaces not only support 3D reconstruction for graphical modeling but also offer features information which is used for augmented reality. Finally, we verify efficiency of the proposed method with demonstration of an augmented reality application using the proposed method.

• 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.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.542-546
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• 2009

This paper introduces a Mixed-Reality based Software technology in Smart-Phone Environment. The field of Mixed-Reality in mobile environment is relatively young. but Cause to develop Mobile infra and improvement of mobile device, open-platform mobile OS, the request extended This paper suggest the method for Marker Detection and Marker Tracking method. This method is the one of some kind of a base-technology in Mixed Reality. this method is to effect to location and registration. This paper suggest the method in low CPU computing power. Using a deformable searching area, the method improve computing power. and Using a Cam-shift algorithm, we suggest a calibration free method.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.123-130
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• 2007

The aim of this study was to propose a fusion and registration method with heterogeneous small animal acquisition system in small animal in-vivo study. After an intravenous injection of $^{18}F$-FDG through tail vain and 60 min delay for uptake, mouse was placed on an acryl plate with fiducial markers that were made for fusion between small animal PET (microPET R4, Concorde Microsystems, Knoxville TN) and Discovery LS CT images. The acquired emission list-mode data was sorted to temporally framed sinograms and reconstructed using FORE rebining and 2D-OSEM algorithms without correction of attenuation and scatter. After PET imaging, CT images were acquired by mean of a clinical PET/CT with high-resolution mode. The microPET and CT images were fusion and co-registered using the fiducial markers and segmented lung region in both data sets to perform a point-based rigid co-registration. This method improves the quantitative accuracy and interpretation of the tracer.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.49-58
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• 2011

Typically, vision-based AR systems operate on the basis of prior knowledge of the environment such as a square marker. The traditional marker-based AR system has a limitation that the marker has to be located in the sensing range. Therefore, there have been considerable research efforts for the techniques known as real-time camera tracking, in which the system attempts to add unknown 3D features to its feature map, and these then provide registration even when the reference map is out of the sensing range. In this paper, we describe a real-time camera tracking framework specifically designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that a real-time camera tracking is achieved on the basis of a plane tracking algorithm. Also we suggest a method for re-detecting features to maintain registration of virtual objects. The proposed method can cope with the problem that the features cannot be tracked, when they go out of the sensing range. The main advantage of the proposed system are not only low computational cost but also convenient. It can be applicable to an augmented reality system for mobile computing environment.