13985475
A clustering-based approach for prediction of cardiac resynchronization therapy
This paper presents a method for predicting pacing sites in the left ventricle of a heart and its result can be used to assist device programming in cardiac resynchronization therapy (CRT), which is a widely adopted therapy for heart failure patients. In a traditional CRT device deployment, pacing sites are selected without quantitative prediction. That runs the risk of suboptimal benefits. In this work, a surface tracking method is proposed to describe the ventricular wall motion and a hierarchical agglomerative clustering technique is applied to radial motion series to find candidate pacing sites. Using clinical MRI data in our experiments, we show that the proposed method performs as well as we expect. Our approach can not only effectively identify suitable pacing sites, but also distinguish patients from normals perfectly to help medical diagnosis.
14826038
A Spatio-Temporal Modeling Method for Shape Representation
The spherical harmonic (SPHARM) description is a powerful surface modeling technique that can model arbitrarily shaped but simply connected three dimensional (3D) objects. Because SPHARM based 3D models can derive functional information analysis and classify different pathological symptoms, it has been used in many applications in biomedical image computing. There is an urgent requirement for efficient spatio-temporal shape modeling to represent the dynamic anatomical structures in many applications (e.g., medical image analysis, geospatial information systems). In this paper we propose a novel real spherical harmonics based spatio-temporal shape modeling method to efficiently and flexibly represent the shapes sequence of anatomical structures in medical images. Our method works well on the simply connected 3D objects and the effectiveness of our approach is demonstrated through theoretic and experimental exploration of a set of medical image applications. Furthermore, an evaluation criterion for spatio-temporal shape modeling efficiency is proposed and the comparison results showed the good performance of our method.
6859814
Three-dimensional Models for Cardiac Bioelectricity Simulation: Cell to Organ
Computer models of the heart have become useful tools in improving understanding of cardiac electrical activation at the cellular level, and in analyzing mechanisms of arrhythmias and antiarrhythmic therapies. In this paper, we propose to use spherical harmonic (SPHARM) surface reconstruction and alignment methods to generate curvilinear meshes for finite element models of ventricular anatomy which incorporate detailed structural information. The endocardial and epicardial surfaces are defined by SPHARM, and the volume between these surfaces is divided into nested shells. Consequently, the resulting mesh comprises hexahedral elements. Using this novel SPHARM-based meshing method, the transmembrane potential propagation is simulated, based on FitzHugh—Nagumo reaction—diffusion equations. The dynamic electrical activation propagations are simulated on realistic cardiac data during a heart cycle. The obtained results clearly demonstrate an accurate resolution of the cardiac potential during the excitation. Our novel curvilinear mesh models have a great potential to be used in an improved simulation of cardiovascular pathologies for testing therapy strategies and planning interventions.
15158980
Large-Scale Modeling of Parametric Surfaces Using Spherical Harmonics
We present an approach for large-scale modeling of parametric surfaces using spherical harmonics (SHs). A standard least square fitting (LSF) method for SH expansion is not scalable and cannot accurately model large 3D surfaces. We propose an iterative residual fitting (IRF) algorithm, and demonstrate its effectiveness and scalability in creating accurate SH models for large 3D surfaces. These large-scale and accurate parametric models can be used in many applications in computer vision, graphics, and biomedical imaging. As a simple extension of LSF, IRF is very easy to implement and requires few machine resources.
2480556
Data Brokers: Building Collections through Automated Negotiation
Collecting digital materials is time-consuming and can gain from automation. Since each source – and even each acquisition – may involve a separate negotiation of terms, a collector may prefer to use a broker to represent his interests with owners. This paper describes the Data Broker Framework (DBF), which is designed to automate the process of digital object acquisition. For each acquisition, a negotiation agent is assigned to negotiate on the collector’s behalf, choosing from strategies in a strategy pool to automatically handle most bargaining cases and decide what to accept and what counteroffers to propose. We introduce NOODLE (Negotiation OntOlogy Description LanguagE) to formally specify terms in the negotiation domain.
15225252
Morphometric Analysis of Hippocampal Shape in Mild Cognitive Impairment: An Imaging Genetics Study
A computational framework is presented for surface based morphometry to localize shape changes between groups of 3D objects. It employs the spherical harmonic (SPHARM) method for surface modeling and random field theory (RFT) for statistical inference. Several new components are introduced to overcome previous limitations: (1) a general linear model is used to facilitate controlling for covariates; (2) a new SPHARM registration method SHREC is proposed to better align SPHARM models; and (3) an estimated smoothness is used in RFT-based analysis to obtain more accurate results. This framework is applied in a mild cognitive impairment (MCI) study to examine hippocampal shape changes related to diagnostic and genetic conditions. Several interesting findings from our analyses suggest combining imaging phenotypes and genetic profiles has the potential to elucidate biological pathways for better understanding MCI and Alzheimer's disease.
27674470
Application of Software Fault Tree Analysis to an Airport Ground Control System
With the ever increasing role of software in our day-to-day life, and even more important the criticality of their role in safety and reliability of the applications, it is important to find techniques that helps with identifying and balancing risks. One such technique is Fault Tree Analysis, which has proven to be powerful in other domains such as systems and processes. This paper, describes the results of application of the fault tree analysis to software requirement specification for an airport ground control system. In addition, this paper proposes a set of guidelines on how to apply SFTA to software requirement specification.
29851215
Unified probabilistic models for face recognition from a single example image per person
This paper presents a new technique of unified probabilistic models for face recognition from only one single example image per person. The unified models, trained on an obtained training set with multiple samples per person, are used to recognize facial images from another disjoint database with a single sample per person. Variations between facial images are modeled as two unified probabilistic models: within-class variations and between-class variations. Gaussian Mixture Models are used to approximate the distributions of the two variations and exploit a classifier combination method to improve the performance. Extensive experimental results on the ORL face database and the authors' database (the ICT-JDL database) including totally 1,750 facial images of 350 individuals demonstrate that the proposed technique, compared with traditional eigenface method and some well-known traditional algorithms, is a significantly more effective and robust approach, for face recognition.
17498280
A Hardware Approach for Reducing Interpretation Overhead
Abstract—An interpreter reads instructions of the source executable and perform each corresponding operation in turn on a software-maintained version of the old ISA’s state. Interpretation has emerged as an important tool with real world applications. Interpretation is always adopted to support instruction set emulation and handle the non-hotspot code in a two-stage dynamic binary translation strategy. An important consideration of an interpreter is the runtime overhead. We investigate that repeated re-decode operations are the bottleneck of interpretation overhead. We propose interpreted code cache (Pcache), a hardware assist, to save the information of the decoded instruction for reuse. We analyze and model Pcache performance via a real interpretation system. Results from SPEC2000 integer benchmarks show that Pcache could significantly reduce re-decode operations and the overhead of interpretation. We demonstrate that the hardware Pcache is a highly effective approach, and the extra overhead is neglectable compared to the performance gains.
15979714
A New Architecture For Multiple-Precision Floating-Point Multiply-Add Fused Unit Design
The floating-point multiply-add fused (MAF) unit sets a new trend in the processor design to speed up floatingpoint performance in scientific and multimedia applications. This paper proposes a new architecture for the MAF unit that supports multiple IEEE precisions multiply-add operation (AtimesB+C) with Single Instruction Multiple Data (SIMD) feature. The proposed MAF unit can perform either one double-precision or two parallel single-precision operations using about 18% more hardware than a conventional double-precision MAF unit and with 9% increase in delay. To accommodate the simultaneous computation of two single-precision MAF operations, several basic modules of double-precision MAF unit are redesigned. They are either segmented by precision mode dependent multiplexers or attached by the duplicated hardware. The proposed MAF unit can be fully pipelined and the experimental results show that it is suitable for processors with floatingpoint unit (FPU).
14935665
Optimal Matrix Computing Using Vector Division with Sub-word Parallel
Available computing is expected to be effective and efficient in ubiquitous multimedia services. And, matrix multiplication is particular to ubiquitous computing such as image transformation so that it is urgent to exploit potential parallelism as well as data reuse in matrix multiplication. Therefore, based on synchronized data triggered architecture (SDTA), we propose a method of parallel vector division (PVD) as well as sub-word parallel (SWP) supported on SDTA to optimize the matrix computation on specified architecture. Experimental results show that PVD with SWP is suitable for matrix multiplication on SDTA instruction set architecture. Besides, we could extend the proposed model into other data-intensive computing on SDTA.