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Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic(More)
Direct numerical simulation (DNS) of turbulence is computationally intensive and typically relies on some form of parallel processing. The authors present techniques to map DNS computations to modern graphics processing units (GPUs), which are characterized by very high memory bandwidth and hundreds of SPMD (single-program-multiple-data) processors.
Implicit representations have the potential to represent large volumes succinctly. In this paper we present a multiresolution and progressive implicit representation of scalar volumetric data using anisotropic Gaussian radial basis functions (RBFs) defined over an octree. Our representation lends itself well to progressive level-of-detail representations.(More)
The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications,(More)
There is no segmentation method that performs perfectly with any dataset in comparison to human segmentation. Evaluation procedures for segmentation algorithms become critical for their selection. The problems associated with segmentation performance evaluations and visual verification of segmentation results are exaggerated when dealing with thousands of(More)
There is a need for tools to classify cells based on their 3D shape. Cells exist in vivo in 3D, cells are frequently cultured within 3D scaffolds in vitro, and 3D scaffolds are used for cell delivery in tissue engineering therapies. Recent work indicates that the physical structure of a tissue engineering scaffold can direct stem cell function by driving(More)
This paper describes our on-going work to accelerate ZENO, a software tool based on Monte Carlo methods (MCMs), used for computing material properties at nanoscale. ZENO employs three main algorithms: (1) Walk on Spheres (WoS), (2) interior sampling, and (3) surface sampling. We have accelerated the first two algorithms. For the sake of brevity, the paper(More)
icons to identify search results. One interesting alternative to this is the use of motion as described by Ware and Bobrow in [14]. In this work, when users move the mouse over a node, nodes within the target node's local neighborhood move in some particular way. This can allow for "pre-attentive coding", which makes objects seem to "pop out" from the(More)
There is a need for tools to classify cells based on their three-dimensional (3D) shape. Cells exist in vivo in 3D, cells are frequently cultured within 3D scaffolds in vitro and 3D scaffolds are used for cell delivery in tissue engineering therapies. Recent work indicates that the physical structure of a tissue engineering scaffold can direct stem cell(More)