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.
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.
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.
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
16998450
Consistent multi-modal non-rigid registration based on a variational approach
In this paper, a novel variational approach for multi-modal image registration based on consistent non-rigid transforms is proposed. The forward and backward transforms are computed in a variational framework simultaneously. A consistency energy is added into the variational registration framework and an iterative method assures that the forward and backward transforms are close approximate inverses of each other. This new scheme can provide more constraints on the forward and backward transforms and make them smoother. This reduces the chance of being stuck into a local minimum. We can incorporate the consistent transforms together with several kinds of information based similarity metrics such as mutual information and correlation ratio into the registration framework. An implicit finite difference scheme is used to solve the Euler-Lagrange equation numerically. Our proposed method is evaluated by using simulated multi-modal magnetic resonance images (MRI) and real medical images. The results of our proposed consistent registration and those using only forward or backward registration are compared. Improvements at the edge area can be easily seen from the registration results.
15580001
On the true Cramer-Rao lower bound for the DA joint estimation of carrier phase and timing offsets
This paper concerns the Cramer-Rao lower bound (CRB) for the data-aided (DA) timing and/or phase recovery, i.e., the synchronization parameter acquisition is aided by a training sequence known to the receiver. For the DA parameter estimation, the CRB typically varies with the training sequence. This indicates that different training sequences offer fundamental different performance. We derive a closed-form formula of the CRB for timing and phase recovery with respect to any particular training sequence. The bound illustrates the close relation between the training sequence and the fundamental limit on timing and phase synchronization. It provides additional insights on the training sequence design.
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.
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.
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.
11558088
A basic stochastic network calculus
A basic calculus is presented for stochastic service guarantee analysis in communication networks. Central to the calculus are two definitions, maximum-(virtual)-backlog-centric (m. b. c) stochastic arrival curve and stochastic service curve, which respectively generalize arrival curve and service curve in the deterministic network calculus framework. With m. b. c stochastic arrival curve and stochastic service curve, various basic results are derived under the (min, +)algebra for the general case analysis, which are crucial to the development of stochastic network calculus. These results include (i)superposition of flows, (ii)concatenation of servers, (iii) output characterization, (iv)per-flow service under aggregation, and (v)stochastic backlog and delay guarantees. In addition, to perform independent case analysis, stochastic strict server is defined, which uses an ideal service process and an impairment process to characterize a server. The concept of stochastic strict server not only allows us to improve the basic results (i)-(v)under the independent case, but also provides a convenient way to find the stochastic service curve of a serve. Moreover, an approach is introduced to find the m.b.c stochastic arrival curve of a flow and the stochastic service curve of a server.