UML在设计模式描述中的应用

设计模式主要用于描述在软件设计过程中不断重复发生的问题以及这些问题的解决方案。UML是一种直观化、明确化、构件和文档化软件系统的通用可视化建模语言。详细介绍了使用UML的各种图形描述设计模式的方法及特点，并通过实例说明了UML在设计模式描述中的优势。     

A general algorithm for optimal sampling schedule design in nuclear medicine imaging

Optimal sampling schedule (OSS) is of great interest in biomedical experiment design, as it can improve the physiological parameter estimation precision and significantly reduce the samples required. A number of well designed algorithms and software packages have been developed, which deal with the instantaneous measurements at discrete times. However, in nuclear medicine tracer kinetic studies, the imaging systems, such as positron emission tomography (PET) and single photon emission computed tomography (SPECT), take measurements (images) based on continuous accumulation over time intervals. In this case, the existing algorithms cannot be used to design OSS so as to reduce the image frame numbers. In this paper, a general OSS design algorithm for the accumulative measurement is proposed. The potential usefulness of the algorithm is demonstrated by its designing OSS in [18F] fluoro-2-deoxy-D-glucose (FDG) studies with PET to estimate the local cerebral metabolic rate of glucose. The robustness of parameter estimation using the OSS with respect to intra-subject and inter-subject parameter variations is also presented.     

功能图像技术与算法的研究和应用

描述了功能图象处理技术的工作原理及医学应用,并着重对目前主要的六种功能图象生成算法进行了论述并加以比较。     

功能图象技术与算法的研究和应用

描述了功能图象处理技术的工作原理及医学应用,并着重对目前主要的六种功能图象生成算法进行了论述并加以比较。     

Three-dimensional feature-preserving noise reduction for real-time electron tomography

Electron tomography (ET) is the leading imaging technique for visualizing the molecular architecture of complex biological specimens. Currently, real-time ET systems allow scientists to acquire experimental datasets with the electron microscope and obtain a preliminary version of the three-dimensional structure of the specimen. In principle, this rough structure allows assessment of the quality of the sample and can also be used as a guide to collect more datasets. However, in practice, the low signal-to-noise ratio of the ET datasets precludes detailed interpretation and makes their assessment difficult. Therefore, noise reduction methods must be integrated in these real-time ET systems for their fully exploitation. This work proposes and evaluates two different multithreaded implementations of a sophisticated noise reduction method with capabilities of preservation of biologically relevant features. The exploitation of the computing power of modern multicore platforms makes this noise reduction method provide datasets appropriate for assessment in a matter of a few minutes, thereby making it suitable for integration in current real-time electron tomography systems.     

Simultaneous multi-modality ROI delineation in clinical practice

The delineation of tumors and their surrounding organs at risk is a critical step of the treatment planning for radiation therapy. Besides computer tomography (CT), other imaging modalities are used to improve the quality of the delineations, such as magnetic resonance imaging (MRI) and positron emission tomography (PET). A practical framework is presented for using multiple datasets from different modalities during the delineation phase. The system is based on two basic principles. First, all image datasets of all available modalities are displayed in their original form (in their own coordinate system, with their own spatial resolution and voxel aspect ratio), and second, delineations can take place on all orthogonal views of each dataset and changes made to a delineation are visualized in all image sets, giving direct feedback to the delineator. The major difference between the described approach and other existing delineation tools is that instead of resampling the image sets, the delineations are transformed from one dataset to another. The transformation used for transferring the delineations is obtained by rigid normalized mutual information registration. The crucial components and the benefits of the application are presented and discussed.     

UML/ROSE在商贸管理系统中的应用

UML是面向对象的标准化建模语言,用于对软件进行描述、可视化处理、构造和建立软件系统的文档。介绍了UML的主要内容,利用统一建模语言UML和它的开发工具ROSE对系统的实现进行分析。使用UML进行软件设计能够提高软件的开发效率。     

大脑多模态成像技术定量研究进展

现代医学成像技术是脑科学研究和脑疾病诊断的利器,不同模态的成像技术提供不同的信息可协同表征脑部结构和功能。其中定量成像技术着眼于和生理、物理相关的内在参量,旨在提供更精准的信息。本文以正电子发射扫描成像(positron emission tomography,PET)和磁共振成像(magnetic resonance imaging,MRI)两种生物医学成像模态为例,针对性地讨论它们在定量刻画大脑微观结构和功能领域的发展状况,目前尚存的关键技术问题和未来的可能发展方向。围绕定量MRI,从表观参数定量开始,介绍其中的单参数定量的现状和不足,以及目前多参数同时定量的发展动态;围绕微观参数定量,介绍针对髓鞘成像的两大方法,包括多组分T2定量和基于超短回波时间髓鞘直接成像,介绍磁共振定量成像特别是磁共振扩散成像的可比较性和可重复性研究。围绕定量PET,从最广泛的代谢动力学模型——房室模型开始介绍,对生理参数与示踪剂摄取量的关系进行了详细描述,展开到定量的误差来源包括模型选择、图像质量以及输入函数测量误差3个方面进行分析,介绍最新进展包括硬件设备、图像重建方法以及定量分析方法。最后对MRI定量...     

动态PET重建中的区域时空先验研究

针对动态正电子发射成像（PET）Bayesian重建,提出一种区域时空先验(RST)模型。RST先验充分利用动态PET序列图像的空间和时间信息,在2维空间和1维时间上对噪声进行双重约束。为验证所提方法的有效性,进行人体脑部18F-FDG动态PET计算机仿真实验。实验结果表明,较其他经典重建方法,通过RST先验的引入,所提方法对于动态PET图像重建质量有着很好的改善,同时提高了病灶区域18F-FDG流入速率Ki估计准确度。     

基于Vega软件的SAR实时仿真技术

进行合成孔径雷达（SAR）成像仿真是研究成像雷达的一个重要手段。本文在分析SAR成像仿真机理的基础上,提出了一种利用视景仿真软件Vega进行SAR实时成像的仿真方法。利用软件平台VC＋＋、Multigen Creator和Vega设计机载合成孔径雷达（SAR）成像仿真系统,分析了影响机载SAR成像质量的各种参数,论述了利用Vega的雷达仿真模块——RadarWorks开发机载SAR成像仿真软件的流程以及整体系统的实现等关键技术。     

MEDITOMO: a high performance software package for 3D SPECT imaging

We describe a parallel software library, named MEDITOMO, designed for processing MEDIcal images obtained by SPECT (single photon emission computed tomography) TOMOgraphic systems. MEDITOMO is the core library of the PSE (problem solving environment) MEDIGRID, oriented to medical imaging analysis, which the authors are currently developing. MEDIGRID is employed in a Grid-computing infrastructure involving clinical departments and research institutes. The algorithms of MEDITOMO are the standard ones that are usually applied in the SPECT analysis, i.e. the conjugate gradient and the expectation maximization. The main contribution of this work concerns the introduction of the total variation seminorm as the edge-preserving regularization in both algorithms and the development of the parallel software library. Experiments carried out on synthetic and clinical data are shown.     

针刺效应的神经影像学研究

介绍了研究针刺机理的神经影像技术方法:fMRI(functional magnetic resonance imaging),PET(positron emission tomography),EEG(electroencephalography)和MEG(magnetoencephalography).介绍了针刺研究中穴位点和对照方法的选取.分别从针刺对于大脑网络、边缘系统和自主神经系统的调节3个方面概述了针刺效应神经生理机制的研究成果.指出了目前的研究所存在的问题,并对未来的研究进行展望.总结和概述了目前针刺效应的神经影像学研究和进展,希望有助于加速针刺机理的研究和认识,早日揭示针刺机理,发扬祖国传统医学.     

Architecture for the next generation system management tools

To get more results or greater accuracy, computational scientists execute their applications on distributed computing platforms such as clusters, grids, and clouds. These platforms are different in terms of hardware and software resources as well as locality: some span across multiple sites and multiple administrative domains, whereas others are limited to a single site/domain. As a consequence, in order to scale their applications up, the scientists have to manage technical details for each target platform. From our point of view, this complexity should be hidden from the scientists, who, in most cases, would prefer to focus on their research rather than spending time dealing with platform configuration concerns.In this article, we advocate for a system management framework that aims to automatically set up the whole run-time environment according to the applications’ needs. The main difference with regards to usual approaches is that they generally only focus on the software layer whereas we address both the hardware and the software expectations through a unique system. For each application, scientists describe their requirements through the definition of a virtual platform (VP) and a virtual system environment (VSE). Relying on the VP/VSE definitions, the framework is in charge of (i) the configuration of the physical infrastructure to satisfy the VP requirements, (ii) the set-up of the VP, and (iii) the customization of the execution environment (VSE) upon the former VP. We propose a new formalism that the system can rely upon to successfully perform each of these three steps without burdening the user with the specifics of the configuration for the physical resources, and system management tools. This formalism leverages Goldberg’s theory for recursive virtual machines (Goldberg, 1973 [6]) by introducing new concepts based on system virtualization (identity, partitioning, aggregation) and emulation (simple, abstraction). This enables the definition of complex VP/VSE configurations without making assumptions about the hardware and the software resources. For each requirement, the system executes the corresponding operation with the appropriate management tool.As a proof of concept, we implemented a first prototype that currently interacts with several system management tools (e.g., OSCAR, the Grid’5000 toolkit, and XtreemOS) and that can be easily extended to integrate new resource brokers or cloud systems such as Nimbus, OpenNebula, or Eucalyptus, for instance.     

RISE++: a symbolic environment for scan-based testing

The architecture and implementation of the Remote Interactive Scan Environment (RISE++), an object-oriented software system that makes use of distributed computing techniques, are discussed. This system supports the development, application, and debugging of scan-based tests for the HP/Apollo Series 10000 RISC workstation and can be used with other scan architectures. RISE++ executes on a separate workstation and communicates with the system under test via a local area network. Test engineers can develop and debug scan tests under RISE++ because it tracks may trivial but important details for them and provides them with precise control over the test hardware     

An optimization-model-based interactive decision support system for regional energy management systems planning under uncertainty

In this study, an interactive decision support system (UREM-IDSS) has been developed based on an inexact optimization model (UREM, University of Regina Energy Model) to aid decision makers in planning energy management systems. Optimization modeling, scenario development, user interaction, policy analysis and visual display are seamlessly integrated into the UREM-IDSS. Uncertainties in energy-related parameters are effectively addressed through the interval linear programming (ILP) approach, improving the robustness of the UREM-IDSS for real-world applications. Thus, it can be used as an efficient tool for analyzing and visualizing impacts of energy and environmental policies, regional/community sustainable development strategies, emission reduction measures and climate change in an interactive, flexible and dynamic context. The Region of Waterloo has been selected to demonstrate the applicability and capability of the UREM-IDSS. A variety of scenarios (including a reference case) have been identified based on different energy management policies and sustainable development strategies for in-depth analysis of interactions existing among energy, socio-economy, and environment in the Region. Useful solutions for the planning of energy management systems have been generated, reflecting complex tradeoffs among energy-related, environmental and economic considerations. Results indicate that the UREM-IDSS can be successfully used for evaluating and analyzing not only the effects of an individual policy scenario, but also the variations between different scenarios compared with a reference case. Also, the UREM-IDSS can help tackle dynamic and interactive characteristics of the energy management system in the Region of Waterloo, and can address issues concerning cost-effective allocation of energy resources and services. Thus, it can be used by decision makers as an effective technique in examining and visualizing impacts of energy and environmental policies, regional/community development strategies, emission reduction measures, and climate change within an integrated and dynamic framework.     

Fast parametric imaging algorithm for dual-input biomedical system parameter estimation

Medical parametric imaging with dynamic positron emission tomography (PET) plays an increasingly potential role in modern biomedical research and clinical diagnosis. The key issue in parametric imaging is to estimate parameters based on sampled data at the pixel-by-pixel level from certain dynamic processes described by valid mathematical models. Classic nonlinear least squares (NLS) algorithm requires a "good" initial guess and the computational time-complexity is high, which is impractical for image-wide parameter estimation. Although a variety of fast parametric imaging techniques have been developed, most of them focus on single input systems, which do not provide an optimal solution for dual-input biomedical system parameter estimation, which is the case of liver metabolism. In this study, a dual-input-generalized linear least squares (D-I-GLLS) algorithm was proposed to identify the model parameters including the parameter in the dual-input function. Monte Carlo simulation was conducted to examine this novel fast algorithm. The results of the quantitative analysis suggested that the proposed technique could provide comparable reliability of the parameter estimation with NLS fitting and accurately identify the parameter in the dual-input function. This method may be potentially applicable to other dual-input biomedical system parameter estimation as well.     

A novel Scan SAR imaging method for maritime surveillance via Lp regularization

In this article, a novel Scan mode synthetic aperture radar (SAR) imaging method for maritime surveillance is presented. Conventional Scan SAR is generally operated with severe azimuth resolution loss in order to cover a large area. The proposed imaging method changes the way Scan SAR illuminates sub-scenes and presents a new radar illuminating strategy based on ships’ spatial distribution in each sub-scene. To gain ships’ spatial distribution, a scene sensing algorithm based on radar range profiles together with a peak-seeking and clustering algorithm is introduced. After that, a Markov transfer-probability matrix is generated to make sure that radar illuminates each sub-scene randomly under the probability we calculated before. Finally, an imaging algorithm within the L_p (0 < p ≤ 1) regularization framework is utilized to reconstruct each sub-scene; the regularization problem is solved by an improved iterative thresholding algorithm. The whole wide swath image is joined by putting all the sub-scenes together. Experimental results support that the proposed imaging method can perform high-resolution wide swath SAR imaging effectively and efficiently without reducing the image resolution.     

Fuzzy clustering based ET image fusion

Electrical tomography (ET) is a technique to visually reconstruct inhomogeneous medium distributions by injecting currents or voltages at the boundary of the medium and measuring the resulted changes in the investigated fields. The ET techniques have been widely used in industrial practices owing to the low cost, rapid response time, non-existent radiation exposure, and non-intrusive characteristics comparing to other tomographic modalities. However, the spatial resolution of ET images using single modality or single-driven patterns (adjacent pattern vs. opposite pattern for imaging reconstruction) is low, which may limit its applications. In this research, the application of fuzzy clustering based fusion techniques for ET imaging is studied. Both multi-modality imaging and multi-driven patterns are of interest. Specifically, two modality images are fused: Electrical Capacitance Tomography (ECT), which performs well for imaging material of large permittivity difference, and Electrical Resistance Tomography (ERT), which is suited for imaging materials having large conductivity differences. The research also explores the fusion of adjacent and opposite patterns for either ECT or ERT modalities. Experiments show that the proposed method can construct high quality ET images by discovering the strong complementary natures of the modalities and/or driven patterns.     

Visual computing for medical diagnosis and treatment

Diagnostic algorithms and efficient visualization techniques are of major importance for preoperative decisions, intra-operative imaging and image-guided surgery. Complex diagnostic decisions are characterized by a high information flow and fast decisions, requiring efficient and intuitive presentation of complex medical data and precision in the visualization. For intra-operative medical treatment, the pre-operative visualization results of the diagnostic systems have to be transferred to the patient on the operation room table. Via augmented reality, additional information of the hidden regions can be displayed virtually. This state-of-the-art report summarizes visual computing algorithms for medical diagnosis and treatment. After starting with direct volume rendering and tagged volume rendering as general techniques for visualizing anatomical structures, we go into more detail by focusing on the visualization of tissue and vessel structures. Afterwards, algorithms and techniques that are used for medical treatment in the context of image-guided surgery, intra-operative imaging and augmented reality are discussed and reviewed.     

The 'Grand Challenge' in Informatics: Engineering Software-Intensive Systems

The science of information and information processing, informatics comprises many areas and includes principles of computing, storing, communicating, and visualizing information, and formalisms to describe information-processing procedures. The development and production of information-processing systems is based on software support systems such as software tools or product data repositories. Software and systems engineering is thus the key discipline for constructing information-processing systems. In particular, software and systems engineering addresses issues such as requirements engineering, architectural design, implementation, reliability engineering, and long-term maintenance. Developing a methodology for specifying and verifying software-intensive systems poses a grand challenge that a broad stream of research must address