2014328
A 3D reconstruction algorithm based on 3D deformable atlas
Reconstructing 3D models from 2D images is an important problem in visualization, particularly in medical and biological visualization. We present a new algorithm for 3D model reconstruction from 2D-images. In our approach, a 3D atlas is deformed to fit the feature data set in the target images. Compared with existing 3D reconstruction techniques, our approach is more efficient and easier to control. The resultant model has good inherent connectivity and smoothness. The resolution of the final model is determined by the resolution of reference model rather than the dataset. The model generates highly detailed view with a limited number of images. This algorithm has been successfully applied to medical simulation.
6725306
Design and Implementation of a Workflow Rendering Engine
Business visualization is an effective tool for business decision making and problem solving. Despite its obvious benefits, 3D visualization is far less common in practice than it should be due to the lack of software support. To address this problem, we have developed a workflow rendering engine that facilitates the 3D visualization of business process information for organizational process analysis and efficiency studies. The workflow information is represented in XML format to be compatible with the new Web graphics standard X3D. The rendering engine is implemented using C++ and OpenGL in order to take full advantage of modern 3D graphics hardware. The object-oriented design makes this engine highly extensible.
8105623
Computerized tumor boundary detection using a Hopfield neural network
The authors present a new approach for detection of brain tumor boundaries in medical images using a Hopfield neural network. The boundary detection problem is formulated as an optimization process that seeks the boundary points to minimize an energy functional based on an active contour model. A modified Hopfield network is constructed to solve the optimization problem. Taking advantage of the collective computational ability and energy convergence capability of the Hopfield network, the authors' method produces the results comparable to those of standard "snakes"-based algorithms, but it requires less computing time. With the parallel processing potential of the Hopfield network, the proposed boundary detection can be implemented for real time processing. Experiments on different magnetic resonance imaging (MRI) data sets show the effectiveness of the authors' approach.
1145290
Hamilton cycles in regular 3-connected graphs
Abstract We show in this paper that for k ⩾63, every 3-connected, k -regular simple graph on at most 22 7 k vertices is hamiltonian.
16064075
Boosting performance of I/O-intensive workload by preemptive job migrations in a cluster system
Load balancing in a cluster system has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, if a significant portion of applications running in the system is I/O-intensive, traditional load balancing policies that focus on CPU and memory usage may cause the system performance to decrease substantially. To solve this problem, a new I/O-aware load-balancing scheme with preemptive job migration is presented to sustain the high performance of a cluster with a diverse set of workload conditions. The proposed scheme dynamically detects I/O load imbalance on nodes of a cluster, and determines whether to preempt some running jobs on overloaded nodes and migrate them to other less- or under-loaded nodes. Besides balancing I/O load, the scheme takes into account both CPU and memory load sharing in clusters, thereby maintaining the same level of performance as existing schemes when I/O load is low or well balanced. Results from a trace-driven simulation show that, compared to the existing approaches that only consider I/O with nonpreemptive job migrations, the proposed schemes achieve the improvement in mean slowdown by up to a factor of 10.
41212780
Real-time rendering of 3D medical data sets
Interactive exploration of three dimension (3D) medical data sets is required by many applications, but the huge amount of computational time and storage space needed for rendering do not allow the visualization of large medical data sets by now. In this paper we present a new algorithm for rendering large medical data sets at interactive frame rates on standard PC hardware. The input data is converted into a compressed hierarchical wavelet representation in a preprocessing step. During rendering, the wavelet representation is decompressed on-the-fly and rendered using hardware texture mapping. The level of detail used for rendering is adapted to the local frequency spectrum of the data and its position relative to the viewer. Using a prototype implementation of the algorithm we were able to perform an interactive walkthrough of large medical data sets on a single of-the-shelf PC.
26735928
I/O Response Time in a Fault-Tolerant Parallel Virtual File System
A fault tolerant parallel virtual file system is designed and implemented to provide high I/O performance and high reliability. A queuing model is used to analyze in detail the average response time when multiple clients access the system. The results show that I/O response time is with a function of several operational parameters. It decreases with the increase in I/O buffer hit rate for read requests, write buffer size for write requests and number of server nodes in the parallel file system, while higher I/O requests arrival rate increases I/O response time.