2,586 research outputs found
Analysis of Image Sequence Data with Applications to Two-Dimensional Echocardiography
Digital two-dimensional echocardiography is an ultrasonic imaging technique that is used as an increasingly important noninvasive technique in the comprehensive characterization of the left ventricular structure and function. Quantitative analysis often uses heart wall motion and other shape attributes such as the heart wall thickness, heart chamber area, and the variation of these attributes throughout the cardiac cycle. These analyses require the complete determination of the heart wall boundaries. Poor image quality and large amount of noise makes computer detection of the boundaries difficult. An algorithm to detect both the inner and outer heart wall boundaries is presented. The algorithm was applied to images acquired from animal studies and from a tissue equivalent phantom to verify the performance. Different approaches to exploiting the temporal redundancy of the image data without making use of results from image segmentation and scene interpretation are explored. A new approach to perform image flow analysis is developed based on the Total Least Squares method. The result of this processing is an estimate of the velocities in the image plane. In an image understanding system, information acquired from related domains by other sensors are often useful to the analysis of images. Electrocardiogram signals measure the change of electrical potential changes in the heart muscle an d provide important information such as the timing data for image sequence analysis. These signals are frequently plagued by impulsive muscle noise and background drift due to patient movement. A new approach to solving these problems is presented using mathematical morphology. Experiments addressing various aspects of the problem, such as algorithm performance, choice of operator parameters, and response to sinusoidal inputs, are reported
Model for an Intelligent Operating System for Executing Tasks on a Reconfigurable Parallel Architecture
Parallel processing is one approach to achieve the large computational processing capabilities required by many real-time computing tasks. One of the problems that must be addressed in the use of reconfigurable multiprocessor systems is matching the architecture configuration to the algorithms to be executed. This paper presents a conceptual model that explores the potential of artificial intelligence tools, specifically expert systems, to design an Intelligent Operating System for multiprocessor systems. The target task is the implementation of image understanding systems on multiprocessor architectures. PASM is used as an example multiprocessor. The Intelligent Operating System concepts developed here could also be used to address other problems requiring real-time processing. An example image understanding task is presented to illustrate the concept of intelligent scheduling by the Intelligent Operating System. Also considered is the use of the conceptual model when developing an image understanding system in order to test different strategies for choosing algorithms, imposing execution order constraints, and integrating results from various algorithms
A Protocol to Develop Practice Guidelines for Primary Care Medical Service Trips
BackgroundNorth American clinicians are increasingly participating in medical service trips (MSTs) that provide primary healthcare in Latin America and the Caribbean. Literature reviews have shown that the existence and use of evidence-based guidelines by these groups are limited, which presents potential for harm.ObjectiveThis paper proposes a 5-step methodology to develop protocols for diagnosis and treatment of conditions encountered by MST clinicians.MethodsWe reviewed the 2010 American College of Physicians guidance statement on guidelines development and developed our own adaptation. Ancestry search of the American College of Physicians statement identified specific publications that provided additional detail on key steps in the guideline development process, with additional focus given to evidence, equity, and local adaptation considerations.FindingsOur adaptation produced a 5-step process for developing locally optimized protocols for diagnosis and treatment of common conditions seen in MSTs. For specified conditions, this process includes: 1) a focused environmental scan of current practices based on grey literature protocols from MST sending organizations; 2) a review of relevant practice guidelines; 3) a literature review assessing the epidemiology, diagnosis, and treatment of the specified condition; 4) an eDelphi process with experts representing MST and Latin American and the Caribbean partner organizations assessing identified guidelines; and 5) external peer review and summary.ConclusionsThis protocol will enable the creation of practice guidelines that are based on best available evidence, local knowledge, and equitable considerations. The development of guidelines using this process could optimize the conduct of MSTs, while prioritizing input from local community partners
FLT3L and Plerixafor Combination Increases Hematopoietic Stem Cell Mobilization and Leads to Improved Transplantation Outcome
AbstractHematopoietic stem cell (HSC) transplantation has curative potential for patients with hematological malignancies. Clinically, HSCs derived from mobilized peripheral blood are used more frequently than bone marrow. However, current standard mobilizing agents yield grafts that may not contain sufficient HSCs. Here, using murine models, we discovered that FLT3L synergized with plerixafor to mobilize phenotypically defined HSCs and their combination (FP) was superior to granulocyte colony-stimulating factor (G-CSF) alone or in combination with plerixafor (GP). Additionally, FP mobilized more regulatory T cells, natural killer cells, and plasmacytoid dendritic cells compared with G-CSF alone or GP. Both syngeneic and allogeneic grafts mobilized by FP led to long-term survival in transplanted mice. Collectively, FP represents a promising novel and potent mobilization regimen with potential clinical application in both the autologous and allogeneic transplantation settings
Steady states in a structured epidemic model with Wentzell boundary condition
We introduce a nonlinear structured population model with diffusion in the
state space. Individuals are structured with respect to a continuous variable
which represents a pathogen load. The class of uninfected individuals
constitutes a special compartment that carries mass, hence the model is
equipped with generalized Wentzell (or dynamic) boundary conditions. Our model
is intended to describe the spread of infection of a vertically transmitted
disease, for example Wolbachia in a mosquito population. Therefore the
(infinite dimensional) nonlinearity arises in the recruitment term. First we
establish global existence of solutions and the Principle of Linearised
Stability for our model. Then, in our main result, we formulate simple
conditions, which guarantee the existence of non-trivial steady states of the
model. Our method utilizes an operator theoretic framework combined with a
fixed point approach. Finally, in the last section we establish a sufficient
condition for the local asymptotic stability of the positive steady state
Focused Ion Beam Microfabrication
Contains an introduction, reports on seven research projects and a list of publications.Defense Advanced Research Projects Agency/U.S. Army Research Office Contract DAAL03-88-K-0108National Science Foundation Grant ECS 89-21728U.S. Army Research Office Contract DAAL03-87-K-0126U.S. Navy - Naval Research Laboratory/Micrion Agreement M08774SEMATEC
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