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Published byErick Mitchell Modified over 9 years ago
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IP / DVR CIBC Image Processing Direct Volume Rendering
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IP / DVR CIBC Image Processing in SCIRun Four primary options: Native SCIRun –Interpolation –Gradient –TransformFieldData Teem (Nrrd, Gage, Tend, …) –N-dim raster data “Swiss Army Knife” –Crop, slice, permute –Local measures (via Gage and Tend) ITK –Similar filtering operations to Teem –Segmentation filters (threshold, confidence-connected, level sets, …) –Registration MATLAB
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IP / DVR CIBC Teem Learn “unu” and “tend” (Verbs of Raster Processing) Decompose Complex Tasks Into Simple Steps Accurate Kernels Derivatives between sample points
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IP / DVR CIBC Teem in SCIRun
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IP / DVR CIBC ITK in SCIRun
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IP / DVR CIBC Direct Volume Rendering Multi-dimensional Transfer Functions Boundaries BioImage More Examples SCIRun Volume Rendering Modules
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IP / DVR CIBC Gordon Kindlmann’s MS Thesis
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IP / DVR CIBC Boundaries
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IP / DVR CIBC Boundaries
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IP / DVR CIBC Boundaries
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IP / DVR CIBC Boundaries
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IP / DVR CIBC Boundaries
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IP / DVR CIBC Tumor Vessel Imaging and Visualization + + + Immobilize. Dose Contrast Optimize Signal : Noise vs Time Discern ContrastDetect Boundaries G. Kindlmann, D. Weinstein, G. Jones, C.R. Johnson, M. Capecchi, and C. Keller. Practical Vessel Imaging by Computed Tomography in Live Transgenic Mouse Models for Human Tumors, Journal of Molecular Imaging, 2005.
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IP / DVR CIBC Volume Rendering: SIMIAN (Joe Kniss)
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IP / DVR CIBC Mouse MRI – Al Johnson - Duke
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IP / DVR CIBC Volume Rendering in SCIRun Texture Objects Gradients Slice Rendering Axis aligned Tangent to view direction Volume Rendering Slice based MIP (max operator) “Direct volume rendering” (over operator)
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IP / DVR CIBC Volume Rendering in SCIRun
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IP / DVR CIBC For More Information: http://www.sci.utah.edu{dmw,jeroen,dav}@sci.utah.eduhttp://www.sci.utah.edu{dmw,jeroen,dav}@sci.utah.edu
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IP / DVR CIBC
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