• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.1074-1077
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• 2002

Biomechanical behavior of the human femur is very important in various clinical situations. In this study, the data of FE models based on DICOM file exported from Computed tomography(CT). We generated FE models(voxel model, tetra model) of human femur using CT slide image. We compared them with Yon Mises stress results derived from finite element analysis(FEA). Comparing the two models, we found a correlation of them. As a result, the tetra model based proposed marching cube algorithm is a valid and accurate method to predict parameters of the complex biomechanical behavior of human femur.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.173-180
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• 2005

This paper proposes an effective algorithm that combines both the stereo matching and the marching cube algorithm. By applying the stereo matching technique to an image obtained from various angles, 3D geometry data are acquired, and using the camera extrinsic parameter, the images are combined. After reconstructing the combined data into mesh using the image index, the normal vector equivalent to each point is obtained and the mesh smoothing is processed. This paper describes the successive processes and techniques on the 3D mesh reconstruction, and by proposing the intermediate iso- surface algorithm. Therefore it improves the 3D data instability problem caused when using the conventional marching cube algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.9
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• pp.148-157
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• 2007

A new method which uses distance fields scheme and marching cube algorithm is proposed in order to get an accurate offset model of arbitrary shapes composed of triangular net. In the method, the space bounding the triangular net is divided into smaller cells. For the efficient calculation of distance fields, valid cells which will generate a portion of offset model are selected previously by the suggested detection algorithm. These valid cells are divided again into much smaller voxels which assure required accuracy. At each voxel distance fields are created by calculating the minimum distances between corner points of voxels and triangular net. After generating the whole distance fields, the offset surface were constructed by using the conventional marching cube algorithm together with mesh smoothing scheme. The effectiveness and validity of this new offset method was demonstrated by performing numerical experiments for the various types of triangular net.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.1
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• pp.28-37
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• 2007

This paper addresses a new surface reconstruction scheme for approximating the isosurface from a set of tomographic cross sectional images. Differently from the novel Marching cube algorithm, our method does not extract iso-density surface(isosurface) directly from the voxels but calculates the iso-density point(isopoint) first. After building the relatively coarse initial mesh by the Cell-boundary algorithm approximating the isosurface, it produces the final isosurface by iteratively shrinking and smoothing the initial mesh. Comparing with the Marching Cube algorithm, our method is robust and does not make any crack in resulting surface model. Furthermore, the proposed method surmounts the O(1)-adjacency limitation of MC in defining the isopoints by permitting the O(2) and O(3)-adjacent isopoints in surface reconstruction, and can produce more accurate isosurface. According to experiments, it is proved to be very robust and efficient for isosurface reconstruction from cross sectional images.

• Journal of KIISE
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• v.43 no.4
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• pp.419-429
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• 2016

Generating a 3D surface model from coronary artery segmentation helps to not only improve the rendering efficiency but also the diagnostic accuracy by providing physiological informations such as fractional flow reserve using computational fluid dynamics (CFD). This paper proposes a method to generate a triangular surface mesh using vessel structure information acquired with coronary artery segmentation. The marching cube algorithm is a typical method for generating a triangular surface mesh from a segmentation result as bit mask. But it is difficult for methods based on marching cube algorithm to express the lumen of thin, small and winding vessels because the algorithm only works in a three-dimensional (3D) discrete space. The proposed method generates a more accurate triangular surface mesh for each singular vessel using vessel centerlines, normal vectors and lumen diameters estimated during the process of coronary artery segmentation as the input. Then, the meshes that are overlapped due to branching are processed by mesh merging and merged into a coronary mesh.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.509-514
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• 2003

The virtual bronchoscopy was implemented using chest CT images to visualize inside of tracheo-bronchial wall. The optical endoscopy procedures are invasive, uncomfortable for patients and sedation or anesthesia may be required. Also, they have serious side effects such as perforation, infection and hemorrhage. In order to determine the navigation path, we segmented the tracheo-bronchial wall from the chest CT image. We used the coordinates as a navigation path for virtual camera that were calculated from medial axis transformation. We used the perspective projection and marching cube algorithm to render the surface from volumetric CT image data. The tracheobronchial disease was classified into tracheobronchial stenosis causing from inflammation or lung cancer, bronchiectasis and bronchial cancer. The virtual bronchoscopy is highly recommended as a diagnosis tool with which the specific place of tracheobronchial disease can be identified and the degree of tracheobronchial disease can be measured qualitatively, Also, the virtual bronchoscopy can be used as an education and training tool for endoscopist and radiologist.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.821-828
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• 2003

The virtual angioscopy was implemented using MR angiography image of carotid artery Inside of the carotid artery is one of the body region not accessible by real optical endoscopy but can be visualized with virtual endoscopy. In order to determine the navigation path, we segmented the common carotid artery and internal carotid artery from the MR angiography image. We used the coordinates as a navigation path for virtual camera that were calculated from medial axis transformation. We used the perspective projection and marching cube algorithm to render the surface from volumetric MRA image data. A stroke occurs when brain cells die because of decreased blood flow to the brain. The carotid artery is the primary blood vessel that supplies the blood flow to the brain. Therefore, the carotid artery stenosis is the primary reason of stroke. The virtual angioscopy is highly recommended as a diagnosis tool with which the specific Place of stenosis can be identified and the degree of stenosis can be measured qualitatively. Also, the virtual angioscopy can be used as an education and training tool for endoscopist and radiologist.

• Tunnel and Underground Space
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• v.18 no.3
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• pp.202-213
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• 2008

In this study, theoretical approach of 3D seismic traveltime tomography was investigated. To guarantee the successful field application of 3D tomography, appropriate control of problem associated with blind zone is pre-requisite. To overcome the velocity distortion of the reconstructed tomogram due to insufficient source-receiver array coverage, the algorithm of 3D seismic traveltime tomography based on the Fresnel volume was developed as a technique of ray-path broadening. For the successful reconstruction of velocity cube, 3D traveltime algorithm was explored and employed on the basis of 2nd order Fast Marching Method(FMM), resulting in improvement of precision and accuracy. To prove the validity and field application of this algorithm, two numerical experiments were performed for globular and layered models. The algorithm was also found to be successfully applicable to field data.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1081-1089
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• 1999

Volume data modeling is concerned with finding a mathematical function which represents the relationship implied by the 3D data. Modeling a volume data geometrically can visualize a volume data using surface graphics without voxelization. It has many merits in that it is fast and requires little memory. We proposes, a method based on wavelet transformation and tetrahedrization. we implement a prototype system based on the proposed method. Last, we evaluated the proposed method comparing it with marching cube algorithm. the evaluation results show that though the proposed method uses only 13% of the volume data, the images generated is as good as the images generated by the marching cubes algorithm.