A Topology Preserving Level Set Method for Geometric Deformable Models
Active contour and surface models, also known as deformable models, are powerful image segmentation techniques. Geometric deformable models implemented using level set methods have advantages over parametric models due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models-the ability to automatically handle topology changes-turns out to be a liability in applications where the object to be segmented has a known topology that must be preserved. We present a new class of geometric deformable models designed using a novel topology-preserving level set method, which achieves topology preservation by applying the simple point concept from digital topology. These new models maintain the other advantages of standard geometric deformable models including subpixel accuracy and production of nonintersecting curves or surfaces. Moreover, since the topology-preserving constraint is enforced efficiently through local computations, the resulting algorithm incurs only nominal computational overhead over standard geometric deformable models. Several experiments on simulated and real data are provided to demonstrate the performance of this new deformable model algorithm.

title: Reconstruction of the human cerebral cortex from magnetic resonance images
abstract: Reconstructing the geometry of the human cerebral cortex from MR images is an important step in both brain mapping and surgical path planning applications. Difficulties with imaging noise, partial volume averaging, image intensity inhomogeneities, convoluted cortical structures, and the requirement to preserve anatomical topology make the development of accurate automated algorithms particularly challenging. Here the authors address each of these problems and describe a systematic method for obtaining a surface representation of the geometric central layer of the human cerebral cortex. Using fuzzy segmentation, an isosurface algorithm, and a deformable surface model, the method reconstructs the entire cortex with the correct topology, including deep convoluted sulci and gyri. The method is largely automated and its results are robust to imaging noise, partial volume averaging, and image intensity inhomogeneities. The performance of this method is demonstrated, both qualitatively and quantitatively, and the results of its application to six subjects and one simulated MR brain volume are presented.

title: Reconstruction of the Central Layer of the Human Cerebral Cortex from MR Images
abstract: Reconstruction of the human cerebral cortex from MR images is a fundamental step in human brain mapping and in applications such as surgical path planning. In a previous paper, we described a method for obtaining a surface representation of the central layer of the human cerebral cortex using fuzzy segmentation and a deformable surface model. This method, however, suffers from several problems. In this paper, we significantly improve upon the previous method by using a fuzzy segmentation algorithm robust to intensity inhomogeneities, and using a deformable surface model specifically designed for capturing convoluted sulci or gyri. We demonstrate the improvement over the previous method both qualitatively and quantitatively, and show the result of its application to six subjects. We also experimentally validate the convergence of the deformable surface initialization algorithm.

title: A 2D moving grid geometric deformable model
abstract: Geometric deformable models based on the level set method have become very popular. To overcome an inherent limitation in accuracy while maintaining computational efficiency, adaptive grid techniques using local grid refinement have been developed for use with these models. However, this strategy requires a very complex data structure, yields large numbers of contour points, and is inconsistent with our previously presented topology-preserving geometric deformable model (TGDM). In this paper, we incorporate an alternative adaptive grid technique called the moving grid method into the geometric deformable model framework. We find that it is simpler to implement than grid refinement, requiring no large, complex, hierarchical data structures. It also limits the number of contour vertices in the final contour and supports the incorporation of the topology-preserving constraint of TGDM. After presenting the algorithm, we demonstrate its performance using both simulated and real images.

title: Gradient vector flow: a new external force for snakes
abstract: Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to concave boundaries, however, have limited their utility. This paper develops a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF) is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The resultant field has a large capture range and forces active contours into concave regions. Examples on simulated images and one real image are presented.

title: Automated Segmentation of Sulcal Regions
abstract: Automatic segmentation and identification of cortical sulci play an important role in the study of brain structure and function. In this work, a method is presented for the automatic segmentation of sulcal regions of cortex. Unlike previous methods that extract the sulcal spaces within the cortex, the proposed method extracts actual regions of the cortical surface that surround sulci. Sulcal regions are segmented from the medial surface as well as the lateral and inferior surfaces. The method first generates a depth map on the surface, computed by measuring the distance between the cortex and an outer “shrink-wrap” surface. Sulcal regions are then extracted using a hierarchical algorithm that alternates between thresholding and region growing operations. To visualize the buried regions of the segmented cortical surface, an efficient technique for mapping the surface to a sphere is proposed. Preliminary results are presented on the geometric analysis of sulcal regions for automated identification.

title: Migration decision for hybrid mobility in reconfigurable distributed virtual machines
abstract: Virtual machine (VM) is an important mechanism to multiplex computer resources. The increasing popularity of network computing has renewed research interests in the adaptive and distributed virtual machines. Service migration is a vital technique to construct reconfigurable VMs. By incorporating mobile agent technology, VM systems can improve their resource utilization, load-balancing and fault-tolerance significantly. This work focuses on the decision problem of hybrid mobility for load-balancing in reconfigurable distributed VMs. We tackle this problem from three aspects: migration candidate determination, migration timing and destination server selection. The service migration timing and destination server selection are formulated as two optimization models. We derive the optimal migration policy for distributed and heterogeneous systems based on stochastic optimization theories. Renewal processes are applied to model the dynamics of migration. We solve the agent migration problem by dynamic programming and extend the optimal service migration decision by considering the interplay of the hybrid mobility. Our decision policy is complementary to the existing service and agent migration techniques. Its accuracy is verified by simulations.

title: A necessary and sufficient condition for a graph G with diameter 5 to be 2-diameter-stable
abstract: A graph G is called an ( l, d )-graph (with respect to edges), if d ( G − E )⩽ d , for each E ⊂ E ( G ) such that | E |⩽ l − 1. The l -diameter-stable graphs are ( l, d )-graphs with diameter d . These two concepts were first proposed by Hartman and Rubin . A necessary and sufficient condition for a graph G with diameter 2 or 3 to be 2-diameter-stable was given in . A necessary and sufficient condition for a graph G with diameter 4 to be 2-diameter-stable was given in . In this paper similar result was obtained for graphs with diameter 5.

title: Distributed shared arrays: A distributed virtual machine with mobility support for reconfiguration
abstract: Distributed Shared Arrays (DSA) is a distributed virtual machine that supports Java-compliant multithreaded programming with mobility support for system reconfiguration in distributed environments. The DSA programming model allows programmers to explicitly control data distribution so as to take advantage of the deep memory hierarchy, while relieving them from error-prone orchestration of communication and synchronization at run-time. The DSA system is developed as an integral component of mobility support middleware for Grid computing so that DSA-based virtual machines can be reconfigured to adapt to the varying resource supplies or demand over the course of a computation. The DSA runtime system also features a directory-based cache coherence protocol in support of replication of user-defined sharing granularity and a communication proxy mechanism for reducing network contention. System reconfiguration is achieved by a DSA service migration mechanism, which moves the DSA service and residing computational agents between physical servers for load balancing and fault resilience. We demonstrate the programmability of the model in a number of parallel applications and evaluate its performance by application benchmark programs, in particular, the impact of the coherence granularity and service migration overhead.

title: Personalized email management at network edges
abstract: A new technique for managing and disseminating Web-based email prefetches messages and generates dynamic pages, displaying them at the network edge. Compared to other popular Web-based email servers, the prefetching and caching emails (PACE) prototype shows an improved performance with respect to user-perceived latency. Additionally, PACE'S centralized neural-network-based personalized spam filter will filter spam and viruses at the server's origin, thus saving bandwidth. Another major concern for users is the email accounts being clogged with spam. Spam filters can be classified as server-side or client-side. Server-side filters are integrated with email servers and filter out spam at the server end.

title: Design and evaluation of an environment APE for automatic parallelization of programs
abstract: In this paper, we present the design and evaluation of a compiler system, called APE, for automatic parallelization of scientific and engineering applications on distributed memory computers. APE is built on top of SUIF compiler. It extends SUIF with capabilities in parallelizing loops with non-uniform cross-iteration dependencies, and in handling loops that have indirect access patterns. We have evaluated the effectiveness of SUIF with several CFD test codes, and found that SUIF handles uniform loops over dense and regular data structures very well. For non-uniform loops, an innovative and efficient parallelization approach based on convex theory have been proposed and is being implemented. We have also presented a class of scalable algorithms for parallel distribution and redistribution of unstructured data structures during parallelizing irregular loops.