1 The architecture and performance of CAVASS (Computer Assisted Visualization and Analysis Software System) George J. Grevera *+ , Jayaram K. Udupa + , Dewey Odhner + , Ying Zhuge + , and Andre Souza + + Medical Image Processing Group Department of Radiology - University of Pennsylvania Philadelphia, PA * Department of Mathematics and Computer Science Saint Joseph’s University
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1 The architecture and performance of CAVASS (Computer Assisted Visualization and Analysis Software System) George J. Grevera *+, Jayaram K. Udupa +, Dewey.
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The architecture and performance of CAVASS (Computer Assisted Visualization
and Analysis Software System)
George J. Grevera*+, Jayaram K. Udupa+, Dewey Odhner+, Ying Zhuge+, and Andre Souza+
+Medical Image Processing GroupDepartment of Radiology - University of Pennsylvania
Philadelphia, PA
*Department of Mathematics and Computer ScienceSaint Joseph’s University
Philadelphia, PA
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Introduction
CAVA: Computer-Aided Visualization and AnalysisCAVASS: CAVA Software System
CAVA deals with the science underlying computerized methods of image processing, analysis, and visualization to facilitate new therapeutic strategies, basic clinical research, education, and training.
Purpose:
To present the architecture and performance of a new cluster-based open-source software system called CAVASS (next incarnation of 3DVIEWNIX).
Goal of CAVASS: To achieve practical processing (image analysis and visualization) time on even very large data sets.
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CAVA Operations in CAVASS
Image processing: for enhancing information about and defining object system in images.
Visualization: for viewing and comprehending object system in its full form, shape, and dynamics.
Manipulation: for altering object system (virtual surgery).
Analysis: for quantifying information about object system.
CAVA operations take object system information from one space to another typically, and eventually also to a quantitative space.
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Previous software systems brought out by our group:
DISPLAY mini computer + frame buffer 1980
DISPLAY82 mini computer + frame buffer 1982 (distributed to > 150 sites with source.)
3D83 GE CT/T 8800 1983 3D98 GE CT/T 9800 1986 3DPC PC-based 1989 3DVIEWNIX Unix, X-Windows 1993 (distributed with source to 100s of sites.)
• Support for a wide variety of data formats (DICOM, GIF, JPEG, PNM, STL, TIFF, VTK)
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Parallelization of CAVA Operations in CAVASS
CAVA operations can be divided into the following three groups.
Type 1: Operation chunk-by-chunk, each chunk accessed only once. Ex: slice interpolation.
Type 2: As in Type 1, but significant further operation needed to combine results. Ex: 3D rendering.
Type 3: Operation chunk-by-chunk, but each chunk may have to be accessed more than once. Ex: graph traversal.
CAVASS parallelizes all three groups of operations.
Divide the input image into chunks and assign each chunk to a processor. A chunk represents data contained in a contiguous set of slices, either image or object structure data.
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ResultsTest Data Sets
Sequential and parallel implementations of several Type 1 and Type 3 operations in CAVASS and ITK/VTK are compared using three data sets:
Regular: 25625646 MR brain image 6 MB
Large: 512512459 CT of thorax 241 MBSuper: 10231023417 CT of head 873 MB
In the following tables, the number of processors used is shown in square brackets under “parallel”. The times reported are in seconds. No entries indicate that the operation was either not tested or not available.