• Composites Research
• /
• v.37 no.1
• /
• pp.40-45
• /
• 2024

In this research, we introduce a novel approach that employs a 3D convolutional neural network (CNN) model to predict the permeability of Gas Diffusion Layers (GDLs). For training the model, we create an artificial dataset of GDL representative volume elements (RVEs) by extracting morphological characteristics from actual GDL images obtained through X-ray tomography. These morphological attributes involve statistical distributions of porosity, fiber orientation, and diameter. Subsequently, a permeability analysis using the Lattice Boltzmann Method (LBM) is conducted on a collection of 10,800 RVEs. The 3D CNN model, trained on this artificial dataset, well predicts the permeability of actual GDLs.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.5 no.1
• /
• pp.13-19
• /
• 2012

In this paper, we propose the pulmonary nodule detection method based on hierarchical 3D block analysis. The proposed system consists of two main part. In the first part, we select the block which is need to analysis. In the second part, we analysis the selected blocks. We extract the shape based features of the object in the selected blocks. Support Vector Machine is applied to the extracted features to classify into nodules and non-nodules.

• Investigative Magnetic Resonance Imaging
• /
• v.18 no.1
• /
• pp.17-24
• /
• 2014

Purpose : To determine whether high-resolution contrast-enhanced three dimensional imaging with spoiled gradient-recalled sequence (HR-CE 3D-SPGR) plays a meaningful role in the assessment of intracranial vertebral artery (ICVA) and posterior inferior cerebellar artery (PICA) in lateral medullary infarction (LMI). Materials and Methods: Twenty-five patients confirmed with LMI were retrospectively enrolled with approval by the IRB of our institute, and 3T MRI with HR-CE 3D-SPGR and contrast-enhanced magnetic resonance angiography (CE-MRA) were performed. Two radiologists who were blinded to clinical information and other brain MR images including diffusion weighted image independently evaluated arterial lesions in ICVA and PICA. The demographic characteristics, the area of LMI and cerebellar involvement were analyzed and compared between patients with arterial lesion in ICVA only and patients with arterial lesions in both ICVA and PICA on HR-CE 3D-SPGR. Results: Twenty-two of twenty-five LMI patients had arterial lesions in ICVA or PICA on HR-CE 3D SPGR. However twelve arterial lesions in PICA were not shown on CE-MRA. Concurrent cerebellar involvement appeared more in LMI patients with arterial lesion in ICVA and PICA than those with arterial lesion in ICVA alone (p = 0.069). Conclusion: HR-CE 3D-SPGR can help evaluate arterial lesions in ICVA and PICA for LMI patients.

• Journal of the Mineralogical Society of Korea
• /
• v.22 no.4
• /
• pp.313-324
• /
• 2009

We explore the effect of particle shape and size on 3-dimensional (3D) network and pore structure of porous earth materials composed of glass beads and silica gel using NMR micro-imaging in order to gain better insights into relationship between structure and the corresponding hydrologic and seismological properties. The 3D micro-imaging data for the model porous networks show that the specific surface area, porosity, and permeability range from 2.5 to $9.6\;mm^2/mm^3$, from 0.21 to 0.38, and from 11.6 to 892.3 D (Darcy), respectively, which are typical values for unconsolidated sands. The relationships among specific surface area, porosity, and permeability of the porous media are relatively well explained with the Kozeny equation. Cube counting fractal dimension analysis shows that fractal dimension increases from ~2.5－2.6 to 3.0 with increasing specific surface area from 2.5 to $9.6\;mm^2/mm^3$, with the data also suggesting the effect of porosity. Specific surface area, porosity, permeability, and cube counting fractal dimension for the natural mongolian sandstone are $0.33\;mm^2/mm^3$, 0.017, 30.9 mD, and 1.59, respectively. The current results highlight that NMR micro-imaging, together with detailed statistical analyses can be useful to characterize 3D pore structures of various porous earth materials and be potentially effective in accounting for transport properties and seismic wave velocity and attenuation of diverse porous media in earth crust and interiors.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2003.06a
• /
• pp.19-22
• /
• 2003

가상현실을 응용한 의료 시뮬레이션은 가상의 3차원 인체모델을 대상으로 위험부담 없이 정확하고 반복적인 훈련 및 교육을 할 수 있는 환경을 제공하기 때문에 의료 시뮬레이션 분야에 도입되어 효과적으로 활용될 수 있다. 본 논문에서는, 사용자와의 상호작용이 가능하고, 기존의 데스크탑 기반 모니터와 테이블 형태의 가상환경 보다 몰입된 가상공간을 체험할 수 있도록 해주는 CAVE$^{TM}$-like 시스템에서의 수술실 환경 프로토타입을 구현하였다. 이를 위하여, 인체의 주요 장기와 뼈를 삼차원 모델로 생성하고, 이 삼차원 모델과 동시에 이에 대한 이차원 단면 영상과 각각의 명칭 및 구조를 설명하는 해부도를 제공하도록 하였다. 또한 실제 수술실과 유사한 환경을 제공해 줌으로써 몰입감을 향상시킨다. 이에 덧붙여 VRML의 센서와 자바 스크립트를 사용하여 인터렉션을 제공하며 보다 현실감 있는 환경을 제공한다

• Journal of Biomedical Engineering Research
• /
• v.25 no.1
• /
• pp.33-41
• /
• 2004

Accuracy of registration between images acquired from various medical image modalities is one of the critical issues in radiation treatment planing. In this study, a method of accuracy evaluation of image registration using a homemade brain phantom was investigated. Chamfer matching of CT-MR and CT-SPECT imaging was applied for the multimodal image registration. The accuracy of image correlation was evaluated by comparing the center points of the inserted targets of the phantom. The three dimensional root-mean-square translation deviations of the CT-MR and CT-SPECT registration were 2.1${\pm}$0.8 mm and 2.8${\pm}$1.4 mm, respectively. The rotational errors were ＜ 2$^{\circ}$ for the three orthogonal axes. These errors were within a reasonable margin compared with the previous phantom studies. A visual inspection of the superimposed CT-MR and CT- SPECT images also showed good matching results.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.160-174
• /
• 2008

In this paper, we propose new coding techniques for photometry data of three-dimensional(3-D) mesh models. We make a good use of geometry and connectivity information to improve coding efficiency of color, normal vector, and texture data. First of all, we determine the coding order of photometry data exploiting connectivity information. Then, we exploit the obtained geometry information of neighboring vortices through the previous process to predict the photometry data. For color coding, the predicted color of the current vertex is computed by a weighted sum of colors for adjacent vortices considering geometrical characteristics between the current vortex and the adjacent vortices at the geometry predictor. For normal vector coding, the normal vector of the current vertex is equal to one of the optimal plane produced by the optimal plane generator with distance equalizer owing to the property of an isosceles triangle. For texture coding, our proposed method removes discontinuity in the texture coordinates and reallocates texture image segments according to the coding order. Simulation results show that the proposed compression schemes provide improved performance over previous works for various 3-D mesh models.

• The Journal of the Korea Contents Association
• /
• v.9 no.11
• /
• pp.309-315
• /
• 2009

Image reconstruction of Inverse Fourier Transform after Frequency Domain Data is filtered applies to Image signal acquired from MR. There are various kinds of image processing techniques; image preprocessing, image reconstruction, image compression, image restoration image mixture, noise and artifact elimination, and image quality improvement. In this paper, optimum filter applicable to diagnosis in clinic by comparing and analyzing the characteristics of the filter will be explained. Fermi-Dirac filter will improve the image quality better than the previous MR image.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.11
• /
• pp.67-76
• /
• 2011

This paper describes the development of interactive visualization techniques and a program that allow us to visualize the structure of the volume data and interactively select and visualize the isosurface components using contour tree. The main characteristic of this technique is to provide an algorithm that draws the contour tree in 2D plane in a way that users easily understand the tree, and to provide an algorithm that can efficiently extract an isosurface component utilizing GPU's parallel architecture. The main characteristic of the program we developed through implementing the algorithms is to provide us with an interactive user interface based on the contour tree for extracting an isosurface component and visualization that integrates with previous isosurface and volume rendering techniques. To show the excelland vof our methods, we applied 3D biomedical volume data to our algorithms. The results show that we could interactively select the isosurface components that represent a polypeptide chain, a ventricle and a femur respectively using the user interface based on our contour tree layout method, and extract the isosurface components with 3x-4x higher speed compared to previous methods.

• Journal of the Korea Computer Graphics Society
• /
• v.3 no.2
• /
• pp.27-34
• /
• 1997

3-D image modeling is in high demand for automated visual inspection and non-destructive testing. It also can be useful in biomedical research, medical therapy, surgery planning, and simulation of critical surgery (i.e. cranio-facial). Image processing and image analysis are used to enhance and classify medical volumetric data. Analyzing medical volumetric data is very difficult In this paper, we propose a new image modeling method based on tetrahedrization to improve the visualization of three-dimensional medical volumetric data. In this method, the trivariate piecewise linear interpolation is applied through the constructed tetrahedral domain. Also, visualization methods including iso-surface, color contouring, and slicing are discussed. This method can be useful to the correct and speedy analysis of medical volumetric data, because it doesn't have the ambiguity problem of Marching Cubes algorithm and achieves the data reduction. We expect to compensate the degradation of an accuracy by using an adaptive sub-division of tetrahedrization based on least squares fitting.