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GTC ON-DEMAND

Presentation
Media
Abstract:
Learn about a new solid modeling approach created to provide support for customer- and patient-specific design and additive manufacturing (3D printing) with graded materials and properties. The new modeling approach involves a hybrid of function-based (implicit) modeling and voxel modeling; models consist of function values on a regular grid (along with a simple interpolant), so meshing/triangulation of objects' surfaces and/or volumes is avoided. Learn the basic ideas behind the modeling approach and see demonstrations of: (1) CUDA-accelerated, real-time interactions between digital models imported from CAD systems and digitized/scanned models, (2) design and fabrication of objects with graded materials/properties, and (3) initial results of CUDA-accelerated methods for mesh-free property evaluation and analysis.
Learn about a new solid modeling approach created to provide support for customer- and patient-specific design and additive manufacturing (3D printing) with graded materials and properties. The new modeling approach involves a hybrid of function-based (implicit) modeling and voxel modeling; models consist of function values on a regular grid (along with a simple interpolant), so meshing/triangulation of objects' surfaces and/or volumes is avoided. Learn the basic ideas behind the modeling approach and see demonstrations of: (1) CUDA-accelerated, real-time interactions between digital models imported from CAD systems and digitized/scanned models, (2) design and fabrication of objects with graded materials/properties, and (3) initial results of CUDA-accelerated methods for mesh-free property evaluation and analysis.  Back
 
Topics:
AEC & Manufacturing, Healthcare and Life Sciences
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7131
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Abstract:
We present two results from CUDA-enabled processing of digitized objects derived from volumetric scans. (1) High-resolution, non-invasive measurement of foot bone motion during walking gait: We compute digitally reconstructed radiographs (DRRs) corresponding to projections of digitized bones and register with stereo fluoroscopy to obtain full 3D kinematics. Images shown include the first results obtained from full scans with multiple bones, overlaps in the projected views, and significant background noise. CUDA-powered algorithms play an essential role in speeding the DRR and registration computations to achieve rates that enable multi-patient studies. (2) Design of swept solids using a CUDA-powered image stack modeler: A multi-axis rotational sweep of a digitized talus is illustrated.
We present two results from CUDA-enabled processing of digitized objects derived from volumetric scans. (1) High-resolution, non-invasive measurement of foot bone motion during walking gait: We compute digitally reconstructed radiographs (DRRs) corresponding to projections of digitized bones and register with stereo fluoroscopy to obtain full 3D kinematics. Images shown include the first results obtained from full scans with multiple bones, overlaps in the projected views, and significant background noise. CUDA-powered algorithms play an essential role in speeding the DRR and registration computations to achieve rates that enable multi-patient studies. (2) Design of swept solids using a CUDA-powered image stack modeler: A multi-axis rotational sweep of a digitized talus is illustrated.  Back
 
Topics:
Medical Imaging & Radiology
Type:
Poster
Event:
GTC Silicon Valley
Year:
2016
Session ID:
P6270
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Abstract:
We present updates on 2 projects using GPU parallelism to achieve crucial performance enhancements: (1) Motion capture via 2D-3D registration: We present the first validated capture of human foot bone motion during walking via registration of CT with bi-plane fluoroscopy. Timing data establishes the crucial role of GPU acceleration. (2) Signed distance grid CAD: We present a novel geometric modeling/digital manufacturing system. New capabilities include real-time collision detection and robust skeletal editing operations.
We present updates on 2 projects using GPU parallelism to achieve crucial performance enhancements: (1) Motion capture via 2D-3D registration: We present the first validated capture of human foot bone motion during walking via registration of CT with bi-plane fluoroscopy. Timing data establishes the crucial role of GPU acceleration. (2) Signed distance grid CAD: We present a novel geometric modeling/digital manufacturing system. New capabilities include real-time collision detection and robust skeletal editing operations.  Back
 
Topics:
Medical Imaging & Radiology, AEC & Manufacturing
Type:
Poster
Event:
GTC Silicon Valley
Year:
2015
Session ID:
P5143
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Abstract:
We present initial results from a marker-free system for measuring bone motion by registering computed 2D projections of 3D bone geometry with stereo pairs of 2D fluoroscope images. Bone geometry is obtained by segmenting 3D CT scan data, and simulated projections (DRRs) are computed using the CUDA-accelerated DRRACC software demonstrated at GTC2013. Bone motion is determined by optimizing correlations of corresponding simulated (DRR) and measured (fluoroscope) 2d image pairs. Results include animations of bone motions, validation of measurement accuracy, and timings for processing data sets.
We present initial results from a marker-free system for measuring bone motion by registering computed 2D projections of 3D bone geometry with stereo pairs of 2D fluoroscope images. Bone geometry is obtained by segmenting 3D CT scan data, and simulated projections (DRRs) are computed using the CUDA-accelerated DRRACC software demonstrated at GTC2013. Bone motion is determined by optimizing correlations of corresponding simulated (DRR) and measured (fluoroscope) 2d image pairs. Results include animations of bone motions, validation of measurement accuracy, and timings for processing data sets.   Back
 
Topics:
Medical Imaging & Radiology
Type:
Poster
Event:
GTC Silicon Valley
Year:
2014
Session ID:
P4173
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Abstract:
We present two applications employing CUDA's 3D texture memory to achieve real-time interaction with volumetric imaging data. Our starting point is an image stack segmented to specify the voxel set for each structure. (1) DRRACC accelerates the computation of digitally reconstructed radiographs (DRRs). Combined with a graphical interface, DRRACC allows a user to select a bone, change its location/orientation, and view the simulated fluoroscope image in real-time. (2) GridModeler is a proof-of-concept CAD system based on an image stack format.
We present two applications employing CUDA's 3D texture memory to achieve real-time interaction with volumetric imaging data. Our starting point is an image stack segmented to specify the voxel set for each structure. (1) DRRACC accelerates the computation of digitally reconstructed radiographs (DRRs). Combined with a graphical interface, DRRACC allows a user to select a bone, change its location/orientation, and view the simulated fluoroscope image in real-time. (2) GridModeler is a proof-of-concept CAD system based on an image stack format.   Back
 
Topics:
Medical Imaging & Radiology, Computer Aided Engineering
Type:
Poster
Event:
GTC Silicon Valley
Year:
2013
Session ID:
P3179
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