Three--dimensional medical imaging: Algorithms and computer systems

This paper presents an introduction to the field of three-dimensional medical imaging It presents medical imaging terms and concepts, summarizes the basic operations performed in three-dimensional medical imaging, and describes sample algorithms for accomplishing these operations. The paper contains a synopsis of the architectures and algorithms used in eight machines to render three-dimensional medical images, with particular emphasis paid to their distinctive contributions. It compares the performance of the machines along several dimensions, including image resolution, elapsed time to form an image, imaging algorithms used in the machine, and the degree of parallelism used in the architecture. The paper concludes with general trends for future developments in this field and references on three-dimensional medical imaging

Virtual Environments Research in the Air Force Institute of Technology Virtual Environments, 3-D Medical Imaging, and Computer Graphics Laboratory

The Air Force Institute of Technology Virtual Environments, 3-D Medical Imaging, and Computer Graphics Laboratory is investigating the 3-D computer graphics, user-interface design, networking protocol, and software architecture aspects of distributed virtual environments. In this paper we describe the research projects that are underway in the laboratory. These projects include the development of an aircraft simulator for a distributed virtual environment, projects for observing, analyzing, and understanding virtual environments, a space virtual environment, a project that incorporates “live” aircraft range data into a distributed virtual environment, a virtual environment application framework, and a project for use in a hospital emergency department. We also discuss the research equipment infrastructure in the laboratory, recent publications, and the educational services we provide

IaDEA: A Development Environment Architecture for Building Generic Intelligent User Interface Agents

The need exists in the work force for generic intelligent user interface agents to address the problem of increasing taskload that is overwhelming the human user. Interface agents could help alleviate user taskload by providing abstractions and intelligent assistance in a self-contained software agent that communicates with the user through the existing user interface and also adapts to user needs and behaviors. The benefits of a generic intelligent user interface agent environment is it can be applied to any highly interactive and information intensive software system from freight and parcel management systems to Wall Street financial investment and analysis. We desire to address the two following difficulties with developing interface agents: (1) The extensive number of existing computer systems makes it impractical to build these agents by hand for each system; (2) Any such agent must be compliant with existing user interface standards and business practices (e.g., the United States..

Gaussian Process Interpolation for Uncertainty Estimation in Image Registration

Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods.Alexander von Humboldt-StiftungNational Alliance for Medical Image Computing (U.S.) (U54-EB005149)Neuroimaging Analysis Center (U.S.) (P41-EB015902)National Center for Image-Guided Therapy (U.S.) (P41-EB015898