• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.439-441
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• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.127-135
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• 2006

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.433-440
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• 2018

Recently, MTV(metabolic tumor volume) has been used as indices of the whole tumor FDG uptake on FDG PET image but it is influenced by image reconstruction. The purpose of this study was to evaluate the correlation between actual volume and metabolic tumor volume applying different SUVmax threshold for different reconstruction algorithm on phantom study. Measurement were performed on a Siemens Biograph mCT40 using a NEMA IEC body phantom containing different size six spheres filled with F18-FDG applying four SBRs (4:1, 8:1, 10:1, 20:1). Images reconstructed four algorithms (OSEM3D, OSEM3D+PSF, OSEM3D +TOF, OSEM3D+TOF+PSF) and MTV were measured with different SUVmax threshold. Overall, the use of increasing thresholds result in decreasing MTV. and increasing the signal to background ratio decreased MTV by applying same SUVmax threshold. The 40% SUVmax threshold gave the best concordance between measured and actual volume in PSF and PSF+TOF reconstruction image. and the 45% threshold had the best correlation between the volume measured and actual volume in OSEM3D and TOF reconstruction image. we believe that this study will be used when the measurement of MTV applying various reconstruction image.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.59-64
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• 2014

This paper presents a method for estimating the bounding volume for image-based 3D object reconstruction. The bounding volume of an object is a three-dimensional space where the object is expected to exist, and the size of the bounding volume strongly affects the resolution of the reconstructed geometry. Therefore, the size of a bounding volume should be as small as possible while it encloses an actual object. To this end, the proposed method uses a set of silhouettes of an object and generates a point cloud using a point filter. A bounding volume is then determined as the minimum sphere that encloses the point cloud. The experimental results show that the proposed method generates a bounding volume that encloses an actual object as small as possible.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.409-417
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• 1999

Talairach atlas consists of three orthogonal sets of coronal, sagittal, and axial slices. This atlas has recently an important role as a standard brain atlas in diagnosing disease related with brain function and analyzing cause of brain disease. The 3D digital volume data set reconstructed from the atlas is widely applied to visualization and quantitative analysis of results processed in the digital computer. This paper represented application method of bi-linear interpolation technique, proposed tri-planar interpolation algorithm for 3D volume data reconstruction of Talairach atlas. And we implemented Talairach atlas editor and discussed problems in volume reconstruction of Talairach atlas. The bi-linear method was applied to only one set of the slices and considered the on intensity value in the interpolation process. The tri-planar technique concurrently uses three orthogonal sets of slices with the same information of brain structures. Talairach atlas editor visualized three sets. of atlas slices on the same coordinate and had editing function. Using the atlas editor, we represented problems in volume reconstruction by showing inconsistency of brain structures among three sets of atlas slices.

• Progress in Medical Physics
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• v.14 no.3
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• pp.167-174
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• 2003

In the radiation treatment planning (RTP) process, especially for stereotactic radiosurgery (SRS), knowing the exact volume and shape and the precise position of a lesion is very important. Sometimes X-ray projection images, such as angiograms, become the best choice for lesion identification. However, while the exact target position can be acquired by bi-projection images, 3D target reconstruction from bi-projection images is considered to be impossible. The aim of this study was to reconstruct the 3D target volume from multiple projection images. It was assumed that we knew the exact target position in advance, and all processes were performed in Target Coordinates, where the origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. The Reconstruction Box was made up of voxels of 3D matrices. Projection images were transformed into 3D in this virtual box using a geometric back-projection method. The resolution and the accuracy of the reconstructed target volume were dependent on the target size. An algorithm was applied to an ellipsoid model and a horseshoe-shaped model. Projection images were created geometrically using C program language, and reconstruction was also performed using C program language and Matlab ver. 6(The Mathwork Inc., USA). For the ellipsoid model, the reconstructed volume was slightly overestimated, but the target shape and position proved to be correct. For the horseshoe-shaped model, reconstructed volume was somewhat different from the original target model, but there was a considerable improvement in determining the target volume.

• ETRI Journal
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• v.44 no.6
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• pp.1034-1046
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• 2022

The learning-based multiview stereo (MVS) methods for three-dimensional (3D) reconstruction generally use 3D volumes for depth inference. The quality of the reconstructed depth maps and the corresponding point clouds is directly influenced by the spatial resolution of the 3D volume. Consequently, these methods produce point clouds with sparse local regions because of the lack of the memory required to encode a high volume of information. Here, we apply the atrous spatial pyramid pooling (ASPP) module in MVS methods to obtain dense feature maps with multiscale, long-range, contextual information using high receptive fields. For a given 3D volume with the same spatial resolution as that in the MVS methods, the dense feature maps from the ASPP module encoded with superior information can produce dense point clouds without a high memory footprint. Furthermore, we propose a 3D loss for training the MVS networks, which improves the predicted depth values by 24.44%. The ASPP module provides state-of-the-art qualitative results by constructing relatively dense point clouds, which improves the DTU MVS dataset benchmarks by 2.25% compared with those achieved in the previous MVS methods.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1472-1480
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• 2021

Image stacking technique is one of the key techniques for complex surface reconstruction. The process includes sample collection, image processing, algorithm editing, surface reconstruction, and finally reaching reliable conclusions. Since this experiment is based on laser scanning confocal microscope to collect the original contour information of the sample, it is necessary to briefly introduce the relevant principle and operation method of laser scanning confocal microscope. After that, the original image is collected and processed, and the data is expanded by interpolation method. Meanwhile, several methods of surface reconstruction are listed. After comparing the advantages and disadvantages of each method, one-dimensional interpolation and volume rendering are finally used to reconstruct the 3D model. The experimental results show that the final 3d surface modeling is more consistent with the appearance information of the original samples. At the same time, the algorithm is simple and easy to understand, strong operability, and can meet the requirements of surface reconstruction of different types of samples.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• Archives of Plastic Surgery
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• v.43 no.5
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• pp.430-437
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• 2016

Background Accurate breast volume assessment is a prerequisite to preoperative planning, as well as intraoperative decision making in breast reconstruction surgery. The use of three-dimensional surface imaging (3D scanning) to assess breast volume has many advantages. However, before employing 3D scanning in the field, the tool's validity should be demonstrated. The purpose of this study was to confirm the validity of 3D-scanning technology for evaluating breast volume. Methods We reviewed the charts of 25 patients who underwent breast reconstruction surgery immediately after total mastectomy. Breast volumes using the Axis Three 3D scanner, water-displacement technique, and magnetic resonance imaging (MRI) were obtained bilaterally in the preoperative period. During the operation, the tissue removed during total mastectomy was weighed and the specimen volume was calculated from the weight. Then, we compared the volume obtained from 3D scanning with those obtained using the water-displacement technique, MRI, and the calculated volume of the tissue removed. Results The intraclass correlation coefficient (ICC) of breast volumes obtained from 3D scanning, as compared to the volumes obtained using the water-displacement technique and specimen weight, demonstrated excellent reliability. The ICC of breast volumes obtained using 3D scanning, as compared to those obtained by MRI, demonstrated substantial reliability. Passing-Bablok regression showed agreement between 3D scanning and the water-displacement technique, and showed a linear association of 3D scanning with MRI and specimen volume, respectively. Conclusions When compared with the classical water-displacement technique and MRI-based volumetry, 3D scanning showed significant reliability and a linear association with the other two methods.