The Experts below are selected from a list of 28842 Experts worldwide ranked by ideXlab platform
Issei Fujishiro - One of the best experts on this subject based on the ideXlab platform.
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Scientific Visualization: Interactions, Features, Metaphors - Previewing Volume Decomposition Through Optimal Viewpoints
2011Co-Authors: Shigeo Takahashi, Issei Fujishiro, Yuriko TakeshimaAbstract:Understanding a Volume Dataset through a 2D display is a complex task because it usually contains multi-layered inner structures that inevitably cause undesirable overlaps when projected onto the display. This requires us to identify feature subVolumes embedded in the given Volume and then visualize them on the display so that we can clarify their relative positions. This article therefore introduces a new feature-driven approach to previewing Volumes that respects both the 3D nested structures of the feature subVolumes and their 2D arrangement in the projection by minimizing their occlusions. The associated process begins with tracking the topological transitions of isosurfaces with respect to the scalar field, in order to decompose the given Volume Dataset into feature components called interval Volumes while extracting their nested structures. The Volume Dataset is then projected from the optimal viewpoint that archives the best balanced visibility of the decomposed components. The position of the optimal viewpoint is updated each time when we peel off an outer component with our interface by calculating the sum of the viewpoint optimality values for the remaining components. Several previewing examples are demonstrated to illustrate that the present approach can offer an effective means of traversing Volumetric inner structures both in an interactive and automatic fashion with the interface.
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automatic cross sectioning based on topological Volume skeletonization
Lecture Notes in Computer Science, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using several examples.
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Smart Graphics - Automatic cross-sectioning based on topological Volume skeletonization
Smart Graphics, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using several examples.
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SIGGRAPH Posters - Automatic cross-sectioning using 3D field topology analysis
ACM SIGGRAPH 2005 Posters on - SIGGRAPH '05, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section’s location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using
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topological Volume skeletonization and its application to transfer function design
Graphical Models \ graphical Models and Image Processing \ computer Vision Graphics and Image Processing, 2004Co-Authors: Shigeo Takahashi, Yuriko Takeshima, Issei FujishiroAbstract:Topological Volume skeletonization is a novel approach for automating transfer function design in visualization by extracting the topological structure of a Volume Dataset. The skeletonization process yields a graph called a Volume skeleton tree, which consists of Volumetric critical points and their connectivity. The resultant graph provides critical field values whose color and opacity are accentuated in the design of transfer functions for direct Volume rendering. Visually pleasing results of Volume visualization demonstrate the feasibility of the present approach.
Luis F Goncalves - One of the best experts on this subject based on the ideXlab platform.
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Four-dimensional fetal echocardiography with spatiotemporal image correlation (STIC): a systematic study of standard cardiac views assessed by different observers.
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine the Federation of Asia and , 2005Co-Authors: Luis F Goncalves, Tinnakorn Chaiworapongsa, Jimmy Espinoza, M L Schoen, Marjorie C Treadwell, Roberto Romero, Wesley Lee, Raywin Huang, Greggory R. Devore, Betsy BeyerAbstract:Objective. To test the agreement between observers and reproducibility of a technique to display standard cardiac views of the left and right ventricular outflow tracts from four-dimensional Volume Datasets acquired with Spatiotemporal Image Correlation (STIC).Methods. A technique was developed to obtain dynamic multiplanar images of the left ventricular outflow tract (LVOT) and right ventricular outflow tract (RVOT) from Volume Datasets acquired with STIC. Volume Datasets were acquired from fetuses with normal cardiac anatomy. Twenty Volume Datasets of satisfactory quality were pre-selected by one investigator. The data was randomly assigned for a blinded review by two independent observers with previous experience in fetal echocardiography. Only one Volume Dataset was used for each fetus. After a training session, the observers obtained standardized cardiac views of the LVOT and RVOT, which were scored on a scale of 1 to 5, based on diagnostic value and image quality (1 = unacceptable, 2 = marginal, 3 =...
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three and four dimensional reconstruction of the aortic and ductal arches using inversion mode a new rendering algorithm for visualization of fluid filled anatomical structures
Ultrasound in Obstetrics & Gynecology, 2004Co-Authors: Luis F Goncalves, Jimmy Espinoza, W Lee, Moshe Mazor, Roberto RomeroAbstract:Three-dimensional (3D) and four-dimensional (4D) sonography have been proposed as adjunctive diagnostic imaging modalities for prenatal diagnosis of congenital heart disease1–24. Here we report 3D and 4D rendering of the aortic and ductal arches using a novel approach to 3D reconstruction of hollow structures (Inversion 3D mode using a Voluson 730 Expert (General Electric Medical Systems Kretztechnik, Zipf, Austria) ultrasound machine and 4DView 2000 version 2.1, General Electric Medical Systems Kretztechnik). This rendering algorithm transforms echolucent structures into solid voxels. Thus, anechoic structures such as the heart chambers, lumen of the great vessels, stomach and bladder appear echogenic on the rendered image, whereas structures that are normally echogenic prior to gray-scale inversion (e.g. bones) become anechoic. Figure 1 shows Volume-rendered images of the aortic and ductal arches of a fetus with normal cardiac anatomy examined at 22 + 2 weeks. The Volume Dataset was acquired with sagittal sweeps through the fetal chest and abdomen using the spatio-temporal image correlation (STIC) technique. 3D reconstruction was performed with a combination of ‘gradient light’ and inversion rendering algorithms. Low threshold and transparency levels were adjusted until the structures of interest were visualized. In this particular case, the transparency level was set to 57, and the low threshold level to 91 (both scales range from 0 to 250). Although we chose to use the gradient light algorithm for better visualization, similar images could be visualized using a combination of ‘X-ray’ and ‘surface smooth’ algorithms, or the surface smooth algorithm alone. This Volume Dataset was rendered with the direction of view set from the right to the left side of the body. As the inversion mode cannot distinguish between blood vessels and other hollow structures (e.g. stomach and gallbladder), the rendered image depicts all anechoic structures contained within the region of interest. This characteristic of the method allowed for simultaneous visualization of the esophagus, ascending aorta, aortic arch, descending aorta, pulmonary artery, ductus arteriosus and superior vena cava in the 3D rendered image. Since the diaphragm is normally visualized as a hypoechoic structure by two-dimensional ultrasound, it appeared as a thin echogenic rim separating the thorax from the abdomen after applying the inversion mode. Abdominal structures depicted in Figure 1 include the portal vein, stomach and a portion of the gallbladder. Four-dimensional rendering of this image can be downloaded from the Journal’s website (Videoclip S1). A case of transposition of the great arteries at 28 weeks is presented in Figure 2. In this image, the anterior vessel represents the aorta. The pulmonary artery courses parallel to the ascending aorta. Left and right branches of the pulmonary artery and the ductus arteriosus are clearly visualized. As this fetus was not swallowing at the time of acquisition, the esophagus was not visualized. The rendering technique used to obtain this image was identical to the one used for Figure 1, except that the transparency and low threshold levels were set to 49 and 106, respectively. Four-dimensional rendering of this image can be downloaded from the Journal’s website (Videoclip S2). In conclusion, we have described the application of 3D and 4D rendering of the outflow tracts and other hollow structures of the thorax and abdomen using the novel inversion mode. Since this technique does not use color or power Doppler sonography as a ‘digital contrast’ to highlight the blood vessels, it does not have the inherent limitations to image reconstruction related to the angle of insonation, temporal resolution, or intensity of the Doppler signal. In addition, the technique does not differentiate blood vessels from other hollow structures. Therefore, the relationships between the fetal heart and great vessels and other fluid-filled non-vascular structures such as the esophagus and stomach can be visualized in
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four dimensional ultrasonography of the fetal heart with spatiotemporal image correlation
American Journal of Obstetrics and Gynecology, 2003Co-Authors: Luis F Goncalves, Tinnakorn Chaiworapongsa, Jimmy Espinoza, M L Schoen, Peter Falkensammer, Marjorie C Treadwell, Roberto RomeroAbstract:Abstract Objective This study was undertaken to describe a new technique for the examination of the fetal heart using four-dimensional ultrasonography with spatiotemporal image correlation (STIC). Study design Volume data sets of the fetal heart were acquired with a new cardiac gating technique (STIC), which uses automated transverse and longitudinal sweeps of the anterior chest wall. These Volumes were obtained from 69 fetuses: 35 normal, 16 with congenital anomalies not affecting the cardiovascular system, and 18 with cardiac abnormalities. Dynamic multiplanar slicing and surface rendering of cardiac structures were performed. To illustrate the STIC technique, two representative Volumes from a normal fetus were compared with Volumes obtained from fetuses with the following congenital heart anomalies: atrioventricular septal defect, tricuspid stenosis, tricuspid atresia, and interrupted inferior vena cava with abnormal venous drainage. Results Volume Datasets obtained with a transverse sweep were utilized to demonstrate the cardiac chambers, moderator band, interatrial and interventricular septae, atrioventricular valves, pulmonary veins, and outflow tracts. With the use of a reference dot to navigate the four-chamber view, intracardiac structures could be simultaneously studied in three orthogonal planes. The same Volume Dataset was used for surface rendering of the atrioventricular valves. The aortic and ductal arches were best visualized when the original plane of acquisition was sagittal. Volumes could be interactively manipulated to simultaneously visualize both outflow tracts, in addition to the aortic and ductal arches. Novel views of specific structures were generated. For example, the location and extent of a ventricular septal defect was imaged in a sagittal view of the interventricular septum. Furthermore, surface-rendered images of the atrioventricular valves were employed to distinguish between normal and pathologic conditions. Representative video clips were posted on the Journal's Web site to demonstrate the diagnostic capabilities of this new technique. Conclusion Dynamic multiplanar slicing and surface rendering of the fetal heart are feasible with STIC technology. One good quality Volume Dataset, obtained from a transverse sweep, can be used to examine the four-chamber view and the outflow tracts. This novel method may assist in the evaluation of fetal cardiac anatomy.
Roberto Romero - One of the best experts on this subject based on the ideXlab platform.
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Four-dimensional fetal echocardiography with spatiotemporal image correlation (STIC): a systematic study of standard cardiac views assessed by different observers.
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine the Federation of Asia and , 2005Co-Authors: Luis F Goncalves, Tinnakorn Chaiworapongsa, Jimmy Espinoza, M L Schoen, Marjorie C Treadwell, Roberto Romero, Wesley Lee, Raywin Huang, Greggory R. Devore, Betsy BeyerAbstract:Objective. To test the agreement between observers and reproducibility of a technique to display standard cardiac views of the left and right ventricular outflow tracts from four-dimensional Volume Datasets acquired with Spatiotemporal Image Correlation (STIC).Methods. A technique was developed to obtain dynamic multiplanar images of the left ventricular outflow tract (LVOT) and right ventricular outflow tract (RVOT) from Volume Datasets acquired with STIC. Volume Datasets were acquired from fetuses with normal cardiac anatomy. Twenty Volume Datasets of satisfactory quality were pre-selected by one investigator. The data was randomly assigned for a blinded review by two independent observers with previous experience in fetal echocardiography. Only one Volume Dataset was used for each fetus. After a training session, the observers obtained standardized cardiac views of the LVOT and RVOT, which were scored on a scale of 1 to 5, based on diagnostic value and image quality (1 = unacceptable, 2 = marginal, 3 =...
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three and four dimensional reconstruction of the aortic and ductal arches using inversion mode a new rendering algorithm for visualization of fluid filled anatomical structures
Ultrasound in Obstetrics & Gynecology, 2004Co-Authors: Luis F Goncalves, Jimmy Espinoza, W Lee, Moshe Mazor, Roberto RomeroAbstract:Three-dimensional (3D) and four-dimensional (4D) sonography have been proposed as adjunctive diagnostic imaging modalities for prenatal diagnosis of congenital heart disease1–24. Here we report 3D and 4D rendering of the aortic and ductal arches using a novel approach to 3D reconstruction of hollow structures (Inversion 3D mode using a Voluson 730 Expert (General Electric Medical Systems Kretztechnik, Zipf, Austria) ultrasound machine and 4DView 2000 version 2.1, General Electric Medical Systems Kretztechnik). This rendering algorithm transforms echolucent structures into solid voxels. Thus, anechoic structures such as the heart chambers, lumen of the great vessels, stomach and bladder appear echogenic on the rendered image, whereas structures that are normally echogenic prior to gray-scale inversion (e.g. bones) become anechoic. Figure 1 shows Volume-rendered images of the aortic and ductal arches of a fetus with normal cardiac anatomy examined at 22 + 2 weeks. The Volume Dataset was acquired with sagittal sweeps through the fetal chest and abdomen using the spatio-temporal image correlation (STIC) technique. 3D reconstruction was performed with a combination of ‘gradient light’ and inversion rendering algorithms. Low threshold and transparency levels were adjusted until the structures of interest were visualized. In this particular case, the transparency level was set to 57, and the low threshold level to 91 (both scales range from 0 to 250). Although we chose to use the gradient light algorithm for better visualization, similar images could be visualized using a combination of ‘X-ray’ and ‘surface smooth’ algorithms, or the surface smooth algorithm alone. This Volume Dataset was rendered with the direction of view set from the right to the left side of the body. As the inversion mode cannot distinguish between blood vessels and other hollow structures (e.g. stomach and gallbladder), the rendered image depicts all anechoic structures contained within the region of interest. This characteristic of the method allowed for simultaneous visualization of the esophagus, ascending aorta, aortic arch, descending aorta, pulmonary artery, ductus arteriosus and superior vena cava in the 3D rendered image. Since the diaphragm is normally visualized as a hypoechoic structure by two-dimensional ultrasound, it appeared as a thin echogenic rim separating the thorax from the abdomen after applying the inversion mode. Abdominal structures depicted in Figure 1 include the portal vein, stomach and a portion of the gallbladder. Four-dimensional rendering of this image can be downloaded from the Journal’s website (Videoclip S1). A case of transposition of the great arteries at 28 weeks is presented in Figure 2. In this image, the anterior vessel represents the aorta. The pulmonary artery courses parallel to the ascending aorta. Left and right branches of the pulmonary artery and the ductus arteriosus are clearly visualized. As this fetus was not swallowing at the time of acquisition, the esophagus was not visualized. The rendering technique used to obtain this image was identical to the one used for Figure 1, except that the transparency and low threshold levels were set to 49 and 106, respectively. Four-dimensional rendering of this image can be downloaded from the Journal’s website (Videoclip S2). In conclusion, we have described the application of 3D and 4D rendering of the outflow tracts and other hollow structures of the thorax and abdomen using the novel inversion mode. Since this technique does not use color or power Doppler sonography as a ‘digital contrast’ to highlight the blood vessels, it does not have the inherent limitations to image reconstruction related to the angle of insonation, temporal resolution, or intensity of the Doppler signal. In addition, the technique does not differentiate blood vessels from other hollow structures. Therefore, the relationships between the fetal heart and great vessels and other fluid-filled non-vascular structures such as the esophagus and stomach can be visualized in
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four dimensional ultrasonography of the fetal heart with spatiotemporal image correlation
American Journal of Obstetrics and Gynecology, 2003Co-Authors: Luis F Goncalves, Tinnakorn Chaiworapongsa, Jimmy Espinoza, M L Schoen, Peter Falkensammer, Marjorie C Treadwell, Roberto RomeroAbstract:Abstract Objective This study was undertaken to describe a new technique for the examination of the fetal heart using four-dimensional ultrasonography with spatiotemporal image correlation (STIC). Study design Volume data sets of the fetal heart were acquired with a new cardiac gating technique (STIC), which uses automated transverse and longitudinal sweeps of the anterior chest wall. These Volumes were obtained from 69 fetuses: 35 normal, 16 with congenital anomalies not affecting the cardiovascular system, and 18 with cardiac abnormalities. Dynamic multiplanar slicing and surface rendering of cardiac structures were performed. To illustrate the STIC technique, two representative Volumes from a normal fetus were compared with Volumes obtained from fetuses with the following congenital heart anomalies: atrioventricular septal defect, tricuspid stenosis, tricuspid atresia, and interrupted inferior vena cava with abnormal venous drainage. Results Volume Datasets obtained with a transverse sweep were utilized to demonstrate the cardiac chambers, moderator band, interatrial and interventricular septae, atrioventricular valves, pulmonary veins, and outflow tracts. With the use of a reference dot to navigate the four-chamber view, intracardiac structures could be simultaneously studied in three orthogonal planes. The same Volume Dataset was used for surface rendering of the atrioventricular valves. The aortic and ductal arches were best visualized when the original plane of acquisition was sagittal. Volumes could be interactively manipulated to simultaneously visualize both outflow tracts, in addition to the aortic and ductal arches. Novel views of specific structures were generated. For example, the location and extent of a ventricular septal defect was imaged in a sagittal view of the interventricular septum. Furthermore, surface-rendered images of the atrioventricular valves were employed to distinguish between normal and pathologic conditions. Representative video clips were posted on the Journal's Web site to demonstrate the diagnostic capabilities of this new technique. Conclusion Dynamic multiplanar slicing and surface rendering of the fetal heart are feasible with STIC technology. One good quality Volume Dataset, obtained from a transverse sweep, can be used to examine the four-chamber view and the outflow tracts. This novel method may assist in the evaluation of fetal cardiac anatomy.
Shigeo Takahashi - One of the best experts on this subject based on the ideXlab platform.
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Scientific Visualization: Interactions, Features, Metaphors - Previewing Volume Decomposition Through Optimal Viewpoints
2011Co-Authors: Shigeo Takahashi, Issei Fujishiro, Yuriko TakeshimaAbstract:Understanding a Volume Dataset through a 2D display is a complex task because it usually contains multi-layered inner structures that inevitably cause undesirable overlaps when projected onto the display. This requires us to identify feature subVolumes embedded in the given Volume and then visualize them on the display so that we can clarify their relative positions. This article therefore introduces a new feature-driven approach to previewing Volumes that respects both the 3D nested structures of the feature subVolumes and their 2D arrangement in the projection by minimizing their occlusions. The associated process begins with tracking the topological transitions of isosurfaces with respect to the scalar field, in order to decompose the given Volume Dataset into feature components called interval Volumes while extracting their nested structures. The Volume Dataset is then projected from the optimal viewpoint that archives the best balanced visibility of the decomposed components. The position of the optimal viewpoint is updated each time when we peel off an outer component with our interface by calculating the sum of the viewpoint optimality values for the remaining components. Several previewing examples are demonstrated to illustrate that the present approach can offer an effective means of traversing Volumetric inner structures both in an interactive and automatic fashion with the interface.
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automatic cross sectioning based on topological Volume skeletonization
Lecture Notes in Computer Science, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using several examples.
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Smart Graphics - Automatic cross-sectioning based on topological Volume skeletonization
Smart Graphics, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using several examples.
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SIGGRAPH Posters - Automatic cross-sectioning using 3D field topology analysis
ACM SIGGRAPH 2005 Posters on - SIGGRAPH '05, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section’s location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using
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topological Volume skeletonization and its application to transfer function design
Graphical Models \ graphical Models and Image Processing \ computer Vision Graphics and Image Processing, 2004Co-Authors: Shigeo Takahashi, Yuriko Takeshima, Issei FujishiroAbstract:Topological Volume skeletonization is a novel approach for automating transfer function design in visualization by extracting the topological structure of a Volume Dataset. The skeletonization process yields a graph called a Volume skeleton tree, which consists of Volumetric critical points and their connectivity. The resultant graph provides critical field values whose color and opacity are accentuated in the design of transfer functions for direct Volume rendering. Visually pleasing results of Volume visualization demonstrate the feasibility of the present approach.
Yuriko Takeshima - One of the best experts on this subject based on the ideXlab platform.
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Scientific Visualization: Interactions, Features, Metaphors - Previewing Volume Decomposition Through Optimal Viewpoints
2011Co-Authors: Shigeo Takahashi, Issei Fujishiro, Yuriko TakeshimaAbstract:Understanding a Volume Dataset through a 2D display is a complex task because it usually contains multi-layered inner structures that inevitably cause undesirable overlaps when projected onto the display. This requires us to identify feature subVolumes embedded in the given Volume and then visualize them on the display so that we can clarify their relative positions. This article therefore introduces a new feature-driven approach to previewing Volumes that respects both the 3D nested structures of the feature subVolumes and their 2D arrangement in the projection by minimizing their occlusions. The associated process begins with tracking the topological transitions of isosurfaces with respect to the scalar field, in order to decompose the given Volume Dataset into feature components called interval Volumes while extracting their nested structures. The Volume Dataset is then projected from the optimal viewpoint that archives the best balanced visibility of the decomposed components. The position of the optimal viewpoint is updated each time when we peel off an outer component with our interface by calculating the sum of the viewpoint optimality values for the remaining components. Several previewing examples are demonstrated to illustrate that the present approach can offer an effective means of traversing Volumetric inner structures both in an interactive and automatic fashion with the interface.
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automatic cross sectioning based on topological Volume skeletonization
Lecture Notes in Computer Science, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using several examples.
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Smart Graphics - Automatic cross-sectioning based on topological Volume skeletonization
Smart Graphics, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using several examples.
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SIGGRAPH Posters - Automatic cross-sectioning using 3D field topology analysis
ACM SIGGRAPH 2005 Posters on - SIGGRAPH '05, 2005Co-Authors: Yuki Mori, Yuriko Takeshima, Shigeo Takahashi, Takeo Igarashi, Issei FujishiroAbstract:Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional Volume Datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section’s location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given Volume Dataset. The application of a Volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional Volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a Dataset. The feasibility of the proposed method is demonstrated using
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topological Volume skeletonization and its application to transfer function design
Graphical Models \ graphical Models and Image Processing \ computer Vision Graphics and Image Processing, 2004Co-Authors: Shigeo Takahashi, Yuriko Takeshima, Issei FujishiroAbstract:Topological Volume skeletonization is a novel approach for automating transfer function design in visualization by extracting the topological structure of a Volume Dataset. The skeletonization process yields a graph called a Volume skeleton tree, which consists of Volumetric critical points and their connectivity. The resultant graph provides critical field values whose color and opacity are accentuated in the design of transfer functions for direct Volume rendering. Visually pleasing results of Volume visualization demonstrate the feasibility of the present approach.
