http://www.sci.utah.edu/gallery2/v/cibc/ en-us Gallery 2 RSS Module, version 1.1.7 Wed, 22 May 2013 10:11:07 -0600 120 http://www.sci.utah.edu/gallery2/d/1386-9/cibc.jpg http://www.sci.utah.edu/gallery2/v/cibc/ http://www.sci.utah.edu/gallery2/v/cibc/iv3d-torso.png.html http://www.sci.utah.edu/gallery2/v/cibc/iv3d-torso.png.html
Example of volume rendering with ImageVis3D of a torso model based on a high resolution CT scan. (courtesy of Siemens Corporate Research, Princeton). By controlling transfer functions, it is possible to identify different
systems (e.g. skeleton, vasculature) and organs (e.g. heart, kidneys and bladder).]]> Nathan Galli photo Fri, 19 Feb 2010 17:19:59 -0700 http://www.sci.utah.edu/gallery2/v/cibc/model_and_sim.tiff.html http://www.sci.utah.edu/gallery2/v/cibc/model_and_sim.tiff.html ]]> Nathan Galli photo Fri, 19 Feb 2010 16:52:32 -0700 http://www.sci.utah.edu/gallery2/v/cibc/Volumetric+Mesh.png.html http://www.sci.utah.edu/gallery2/v/cibc/Volumetric+Mesh.png.html ]]> Nathan Galli photo Fri, 19 Feb 2010 17:08:46 -0700 http://www.sci.utah.edu/gallery2/v/cibc/Medial+Axis.png.html http://www.sci.utah.edu/gallery2/v/cibc/Medial+Axis.png.html ]]> Nathan Galli photo Fri, 19 Feb 2010 17:07:43 -0700 http://www.sci.utah.edu/gallery2/v/cibc/Material+Boundaries.png.html http://www.sci.utah.edu/gallery2/v/cibc/Material+Boundaries.png.html ]]> Nathan Galli photo Fri, 19 Feb 2010 17:07:43 -0700 http://www.sci.utah.edu/gallery2/v/cibc/Distributed+Particles.png.html http://www.sci.utah.edu/gallery2/v/cibc/Distributed+Particles.png.html ]]> Nathan Galli photo Fri, 19 Feb 2010 17:07:43 -0700 http://www.sci.utah.edu/gallery2/v/cibc/joe-5.png.html http://www.sci.utah.edu/gallery2/v/cibc/joe-5.png.html
<para>Visualization users are increasingly in need of techniques for assessing quantitative uncertainty and error in the images produced. Statistical segmentation algorithms compute these quantitative results, yet volume rendering tools typically produce only qualitative imagery via transfer functionbased classification. These images demonstrate a visualization technique that allows users to interactively explore the uncertainty, risk, and probabilistic decision of surface boundaries. Our approach makes it possible to directly visualize the combined "fuzzy" classification results from multiple segmentations by combining these data into a unified probabilistic data space. </p>
<p>The image above shows a comparison of rendering profiles. Subfigure (A) shows a "fuzzy" volume rendering color-mapped based on a log-scale discriminant (lambda) for white matter. Subfigure (B) shows the risk-surface (lambda equal 0) for white matter color-mapped based on sensitivity (change in boundary position per unit change in importance). Subfigure (C) shows confidence intervals based on percent change in importance.</p>]]> Nathan Galli photo Fri, 12 Feb 2010 12:30:36 -0700 http://www.sci.utah.edu/gallery2/v/cibc/joe-3.png.html http://www.sci.utah.edu/gallery2/v/cibc/joe-3.png.html
Visualization users are increasingly in need of techniques for assessing quantitative uncertainty and error in the images produced. Statistical segmentation algorithms compute these quantitative results, yet volume rendering tools typically produce only qualitative imagery via transfer functionbased classification. These images demonstrate a visualization technique that allows users to interactively explore the uncertainty, risk, and probabilistic decision of surface boundaries. Our approach makes it possible to directly visualize the combined "fuzzy" classification results from multiple segmentations by combining these data into a unified probabilistic data space.]]> Nathan Galli photo Fri, 12 Feb 2010 12:27:43 -0700 http://www.sci.utah.edu/gallery2/v/cibc/xt_stsurf_05.png.html http://www.sci.utah.edu/gallery2/v/cibc/xt_stsurf_05.png.html
Visualization of the return current in the chest (Utah Torso data set) obtained by forward calculation. The boundary values for this computation are provided by measurements of the electrical potential done by B. Taccardi on the cardiac surface. The computation itself was carried out by F. Sachse. A smooth electric current field was derived from the electric potential. Then stream stream surfaces were computed along that current. The stream surfaces are started along isopotential lines on the surface of the heart and advected until they return to the heart, following the typical bent shape induced by the dipolar sources in the heart. The color coding shows the distortion of the parameterization of the start curve. The strength of these images is to improve on previous visualizations based on streamlines since whole volumes can now be identified, and to offer a means to better understand the relationship between in- and outflow of the electric current on the surface of the heart. Additionally, an LIC representation of the electric current was calculated constrained to the cardiac surface.]]> Nathan Galli photo Fri, 19 Feb 2010 14:45:00 -0700 http://www.sci.utah.edu/gallery2/v/cibc/xt_stsurf_04.png.html http://www.sci.utah.edu/gallery2/v/cibc/xt_stsurf_04.png.html
Visualization of the return current in the chest (Utah Torso data set) obtained by forward calculation. The boundary values for this computation are provided by measurements of the electrical potential done by B. Taccardi on the cardiac surface. The computation itself was carried out by F. Sachse. A smooth electric current field was derived from the electric potential. Then stream stream surfaces were computed along that current. The stream surfaces are started along isopotential lines on the surface of the heart and advected until they return to the heart, following the typical bent shape induced by the dipolar sources in the heart. The color coding shows the distortion of the parameterization of the start curve. The strength of these images is to improve on previous visualizations based on streamlines since whole volumes can now be identified, and to offer a means to better understand the relationship between in- and outflow of the electric current on the surface of the heart. Additionally, an LIC representation of the electric current was calculated constrained to the cardiac surface.]]> Nathan Galli photo Fri, 19 Feb 2010 14:45:00 -0700