26210485
Robust Registration of 3-D Ultrasound Images Based on Gabor Filter and Mean-Shift Method
A novel robust method is presented for the registration of 3-D ultrasound images. The proposed method improves the performance of the voxel property-based affine registration in two aspects. First, a set of wavelet-like Gabor filters is used to extract the texture and edge features of the voxels. By using these features, the smoothness of the similarity function in large scale can be improved. Furthermore, adopting edge information can improve the registration accuracy. Second, a robust maximization method based on the mean-shift algorithm and Powell’s direction set method is proposed. The implicitly embedded smoothing process of the mean-shift algorithm can effectively remove the local fluctuation of the similarity function and significantly improve the robustness of optimization. Experimental results demonstrate the robust and accurate performance of the proposed method in the registration of 3-D ultrasound fetal head images.
22330856
Shape Alignment by Learning a Landmark-PDM Coupled Model
This paper revisits the model-based approaches for groupwise shape alignment. The key contribution is modeling the landmarks instead of considering them as nodes sliding along the shape contour. The shape group is thus modeled by a landmark-PDM coupled model instead of a constrained point distribution model (PDM). This coupled model is estimated by a stable four-stage estimation algorithm. There are two significant achievements. First, shapes are aligned in a fully unsupervised manner - both the number and location of landmarks are automatically decided. Second, extremely noisy and largely deformed shapes can be robustly aligned. These are demonstrated using both synthesized and real data
2341708
Segmentation of kidney from ultrasound images based on texture and shape priors
This work presents a novel texture and shape priors based method for kidney segmentation in ultrasound (US) images. Texture features are extracted by applying a bank of Gabor filters on test images through a two-sided convolution strategy. The texture model is constructed via estimating the parameters of a set of mixtures of half-planed Gaussians using the expectation-maximization method. Through this texture model, the texture similarities of areas around the segmenting curve are measured in the inside and outside regions, respectively. We also present an iterative segmentation framework to combine the texture measures into the parametric shape model proposed by Leventon and Faugeras. Segmentation is implemented by calculating the parameters of the shape model to minimize a novel energy function. The goal of this energy function is to partition the test image into two regions, the inside one with high texture similarity and low texture variance, and the outside one with high texture variance. The effectiveness of this method is demonstrated through experimental results on both natural images and US data compared with other image segmentation methods and manual segmentation.
35554419
An Adaptive Enhancement Method for Ultrasound Images
In this paper, we present a novel adaptive method for ultrasound (US) image enhancement. It is based on a new measure of perceptual saliency and the view-dependent feature on US images. By computing this measure on an US image, speckle noise is reduced and perceptual salient boundaries of organs are enhanced. Because of the curvature gradient based saliency measure, this method can enhance more types of salient structures than the well-known saliency network method. Meanwhile, the proposed method does not depend on the closure measure. This makes it more appropriate to enhance real images than other existing methods. Moreover, the local analysis of speckle patterns leads a good performance in speckle reduction for US images. Experimental results show the proposed enhancement approach can provide a good assistant for US image segmentation and image-guided diagnosis.
62556261
An enhanced appearance model for ultrasound image segmentation
Active appearance model (AAM) had been popular on object segmentation for medical images. However, its performance is not good on ultrasound (US) images. In this paper, we propose an enhanced appearance model which represents the texture by edge structure and reduces the view-dependent feature of US images by a novel data normalization process. In our experiments on general US data, the proposed model shows considerable improvements compared to the original one.
119964309
Geodesic closest point constrained inter-subject non-rigid registration
In this paper, we propose an inter-subject brain registration method by combining the intensity and the geodesic closest point based similarity metric. Each of the brain hemispheres can be topologically equalized into a sphere. The inter subject variance can be better reduced by using cortical surface based analysis method. A one to one mapping of the points on spherical surfaces of two subjects can be achieved by using this technique. We find the geodesic correspondence between subjects by using spherical registration first, then the correspondence on the cortical surface between subjects are used to guide the volumetric inter-subject registration. By adding these anatomical constraints of the cortical surface, the inter-subject registration result is more anatomically meaningful and accurate. The cortical surface correspondence between subjects can be combined with the general non-rigid registration. In our experiments, the proposed method performs better than the method of Hartkens et al.
15612889
Keyframe Retrieval by Keypoints: Can Point-to-Point Matching Help?
Bag-of-words representation with visual keypoints has recently emerged as an attractive approach for video search. In this paper, we study the degree of improvement when point-to-point (P2P) constraint is imposed on the bag-of-words. We conduct investigation on two tasks: near-duplicate keyframe (NDK) retrieval, and high-level concept classification, covering parts of TRECVID 2003 and 2005 datasets. In P2P matching, we propose a one-to-one symmetric keypoint matching strategy to diminish the noise effect during keyframe comparison. In addition, a new multi-dimensional index structure is proposed to speed up the matching process with keypoint filtering. Through experiments, we demonstrate that P2P constraint can significantly boost the performance of NDK retrieval, while showing competitive accuracy in concept classification of broadcast domain.
43859012
Dynamic parallel query processing for distributed objects
An effective exploitation of distributed computing environments to improve the performance of large advanced database applications requires parallel query processing techniques. This is because parallel query execution can be achieved by operations of pipelining and data partitioning, as well as independent subqueries. In order to develop efficient parallel query services in distributed environments, we present a query optimization, a dynamic parallel query scheduling algorithm, and an implementation mechanism for querying distributed objects. Our proposal has four important features. First, the query schedule dynamically schedules independent subqueries in parallel. Second, distributed processors are allowed to execute independent subqueries in random. Third, it doesn't limit the number of processors to deal with parallel query processing in a network based computing environment. Fourth, it provides simple operations to synchronize parallel query programs. We give the query optimization for parallel processing, show an algorithm of dynamic parallel query scheduling, describe an implementation method for the parallel query processing in a network-based distributed computing environment, and present the design of communication and synchronization for the parallel query processing.
26702978
Relationship between guaranteed rate server and latency rate server
To analyze scheduling algorithms in computer networks, two models have been proposed and widely used in the literature, namely the Guaranteed Rate (GR) server model and the Latency Rate (LR) server model. While a lot scheduling algorithms have been proved to belong to GR or LR or both, it is not clear what is the relationship between them. The purpose of this paper is to investigate this relationship. We prove that if a scheduling algorithm belongs to GR, it also belongs to LR and vice versa. In addition, we review several other models that are also used for analysis of scheduling algorithms and discuss their relationship with LR model and GR model.
206754760
Per-domain packet scale rate guarantee for expedited forwarding
The expedited forwarding per-hop behavior (EF PHB) was recently replaced by a new definition, called packet scale rate guarantee (PSRG), under the Differentiated Services (DiffServ) framework. This replacement raises two challenges. One is the implementation of a PSRG server. Another is the provision of per-domain PSRG. Specifically, for the former, an open issue is whether hierarchical schedulers can provide PSRG; for the latter, it is not clear whether and how per-domain PSRG can be provided in the presence of flow aggregation. Since, in DiffServ networks, flow aggregation is a natural phenomenon and hierarchical scheduling is high-likely desired, these two challenges become even more critical. To address the first challenge, we introduce a new concept called latency-rate worst-case service guarantee (LR-WSG). We prove that, if a server provides LR-WSG, it also provides PSRG. We show that many well-known schedulers support LR-WSG, which include not only one-level schedulers but also their hierarchical versions. To address the second challenge, we first prove that PSRG can be extended from per-node to per-domain if no flow aggregation is performed. The proof is notable in that it depends solely on the concept of PSRG itself. We then investigate the provision of per-domain PSRG in presence of flow aggregation. We propose to use packet scale fair aggregator (PSFA) to aggregate flows. We show that, with PSFA, per-domain PSRG can be provided in spite of flow aggregation. We finally provide a brief discuss on the viability of using PSFA in DiffServ networks and define an expedited forwarding per-domain behavior (EF PDB).
6410925
Effects of Low-Quality Computation Time Estimates in Policed Schedulers
Researchers conducting computer simulations can often provide estimates of computation time for a given type of simulation, which may be used by the compute cluster to aid in resource allocation and scheduling. However, the low quality of these estimates can cause deadline misses and unpredictable behavior. This problem is exacerbated on complex compute resources, clusters, and grids. Past-deadline jobs may be killed to provide resources for others, but the effect on the throughput of whole batches not fully understood. In this paper, we examine models for simple job schedulers and examine the quality of the deadline guarantee given. Simulation results based on actual runtimes are provided and discussed