626014
The use of hybrid models to recover cardiac wall motion in tagged MR images
We present a new algorithm for the automatic recovery of tag grid-line intersections in Tagged MR images of the left ventricle of the heart. Our method uses an active spring mesh to capture local properties of the motion and a global motion model to capture the global coherence of the motion. We recover the global component of the motion using robust estimation. Different motion models have been developed for short and long axis views of the heart. The algorithm has been tested on healthy and pathological data.
5097328
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
The problem of segmenting an image into separate regions and tracking them over time is one of the most significant problems in vision. Terzopoulos et al. (1987) proposed an approach to detect the contour regions of complex shapes, assuming a user selected initial contour not very far from the desired solution. We propose to further explore the information provided by the user's selected points and apply an optimal method to detect contours which allows a segmentation of the image. The method is based on dynamic programming (DP), and applies to a wide variety of shapes. It is exact and not iterative. We also consider a multiscale approach capable of speeding up the algorithm by a factor of 20, although at the expense of losing the guaranteed optimality characteristic. The problem of tracking and matching these contours is addressed. For tracking, the final contour obtained at one frame is sampled and used as initial points for the next frame. Then, the same DP process is applied. For matching, a novel strategy is proposed where the solution is a smooth displacement field in which unmatched regions are allowed while cross vectors are not. The algorithm is again based on DP and the optimal solution is guaranteed. We have demonstrated the algorithms on natural objects in a large spectrum of applications, including interactive segmentation and automatic tracking of the regions of interest in medical images. >
11252982
Segmentation of range images as the search for geometric parametric models
Segmentation of range images has long been considered in computer vision as an important but extremely difficult problem. In this paper we present a new paradigm for the segmentation of range images into piecewise continuous surfaces. Data aggregation is performed via model recovery in terms of variable-order bi-variate polynomials using iterative regression. Model recovery is initiated independently in regularly placed seed regions in the image. All the recovered models are potential candidates for the final description of the data. Selection of the models is defined as a quadratic Boolean problem, and the solution is sought by the WTA (winner-takes-all) technique, which turns out to be a good compromise between the speed of computation and the accuracy of the solution. The overall efficiency of the method is achieved by combining model recovery and model selection in an iterative way. Partial recovery of the models is followed by the selection (optimization) procedure and only the “best” models are allowed to develop further.The major novelty of the approach lies in an effective combination of simple component algorithms, which stands in contrast to methods which attempt to solve the problem in a single processing step using sophisticated means. We present the results on several real range images.
14750394
Global models with parametric offsets as applied to cardiac motion recovery
We introduce a new solid shape model formulation that includes built-in offsets from a base global component (e.g. an ellipsoid) which are functions of the global component's parameters. The offsets provide two features. First, they help to form an expected model shape which facilitates appropriate model data correspondences. Second, they scale with the base global model to maintain the expected shape even in the presence of large global deformations. We apply this model formulation to the recovery of 3-D cardiac motion from a volunteer dataset of tagged-MR images. The model instance is a variation of the hybrid volumetric ventriculoid (HVV), a deformable thick-walled ellipsoid model resembling the left ventricle (LV) of the heart. A unique aspect of of implementation is the employment of constant volume constraints when recovering the cardiac motion. In addition, we present a novel geodesic-like prismoidal tessellation of the model which provides for more stable fits.
14869645
Multi-modality model-based registration in the cardiac domain
Recent advances in CT technology have made possible the acquisition of high resolution images of the heart in which important anatomical features such as the coronary vessels are visible. The state of the art in MR Imaging techniques, on the other hand, typically provides lower resolution but can facilitate the differentiation of viable (healthy) cardiac tissue from infarcted (injured) tissue. The registration of CT and MR images of the same heart permit the association of anatomy with function. As an example, given an infarcted region, the coronary vessels responsible for irrigating that region may be isolated and targeted for treatment (e.g., coronary bypass). We demonstrate a software package, PROTEUS, which is capable of registering CT and MR images. Since the manifestation of cardiac tissue in the two modalities differs so greatly we rely on features to perform the matching. Specifically, we employ a model-based approach that relies on segmented contours delineating the inner and outer borders of the left ventricle (LV). Given these contours, our technique is completely automatic.
38069956
Introduction to the Special Issue on Innovative Applications of Computer Vision
62621279
Estimating Internet Users' Demand Characteristics
We investigate two parametric approaches and one non-parametric approach toestimating Internet users' value-of-time, an important characteristic ofdemand for Internet services. The advantages of these approaches are madeclear and their limitations discussed. The models are tested with datagenerated from our similation model of the Internet economy. Given thecharacteristics of the data, we investigate parametric count-data modelsfirst. While reasonably good results are obtained on all medium- andlarge-sized jobs, the method fails on small-sized ones. Second, we develop anonparametric quasi-Bayesian update algorithm for retrieving the underlyingdistribution function of Internet users' value-of-time purely fromobservations on their choices. Compared with the parametric count-data models,good results are obtained in every case.
14748622
Power Efficient Algorithms for Computing Fast Fourier Transform over Wireless Sensor Networks
Collaborative signal processing is one of the most promising applications that are currently being investigated for sensor networks. In this paper, we use FFT computation as a vehicle to highlight the issues involved in realizing distributed computations over sensor networks that have global and local communication and synchronization characteristics. We present a power efficient algorithm for computing 1-D Fast Fourier Transform (FFT) over single and multi-hop wireless sensor networks. The proposed algorithm reduces the number of transmissions, eliminates typical redundant computations in a distributed FFT algorithm and uniformly maps complex multiplications over all the sensors nodes by introducing an extra bit-complement permutation stage after first (log2N)/2 iterations. We show that the proposed algorithm improves energy consumption by 36% on the average on multi-hop sensor networks. This saving in energy consumption significantly improves the battery life of the sensor nodes thereby increasing lifetime of the sensor network.
321445
Detection of Masquerade Attacks on Wireless Sensor Networks
We propose two lightweight techniques to detect masquerade attacks on wireless sensor networks (WSN). Our solutions take into consideration, important WSN properties like coverage, connectivity, data aggregation and specific communication patterns. The two proposed techniques complement each other when used concurrently. The mutual guarding (MG) technique does not work when nodes are not completely covered by their neighbors or when adversary has shorter transmission range than the sensor nodes. It also does not protect nodes near the boundary. The SRP technique does not have these drawbacks. In this paper, we present our proposed techniques and analyze their performance in terms of successful masquerade detection rate and traffic and computational overhead.
17420676
A workstation's communication performance benchmark
In this paper we propose a communication benchmark suite: BTU(Bits To the User). In the BTU benchmarking process, the vendor supplies a workstation running a UNIX* operating system, we install our benchmark program and connect the workstation to a testbed which emulates a LAN/WAN environment. The benchmark run will submit the workstation to a carefully designed combination of tests. The result is a predictor of what the user, at the application level, can expect in terms of bits sent to or received from a remote host. Our benchmark takes into account concurrent activities such as CPU and I/O activities which compete for resources on the test machine. The combination of these activities and concurrent activities on the network will interfere with the test machine’s communication performance. The automated BTU benchmark test suite produces results at various levels of abstractions ranging from a single number, characterizing average performance in the style of SPEC92, to a TCP time sequence chart for abnormal behaviors. We intend to serve the user of a workstation by providing information which should enable the users to make a reasonable judgment when acquiring a workstation with a specific configuration within certain cost constraints. Our results when used along with existing benchmarks will make a powerful combination for predicting overall performance. Neither price nor SPECmarks are as good a predictor of communication performance as that measured by BTUs. We conclude this paper with a discussion of extensions to faster networks and our plans for having the community accept this proposal as a communication benchmark.
17233820
IT-enabled transparent electronic markets: the case of the air travel industry
The electronic market hypothesis predicts that by reducing coordination costs, information technology (IT) will shift industrial organization from hierarchical to market-based forms of economic activity. While academic researchers and practitioners have witnessed these shifts with the advent of the Internet, there is little understanding about the process and the underlying forces that drive them. In this paper, we provide an in-depth analysis of the air travel industry, which has recently experienced significant IT-driven transformations. We conclude that, together with IT, pro-competitive laws and the information-intensive nature of air travel products have triggered competition for consumers with transparent market mechanisms, which is leading to the emergence of more transparent electronic markets in the air travel industry.