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检索条件"任意字段=Conference on Visualization in Biomedical Computing"

共 893 条记录，以下是681-690 订阅

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Generalized regression neural networks for biomedical image interpolation

Generalized regression neural networks for biomedical image ...

引用

International Joint conference on Neural Networks (IJCNN)

作者： M.P. Wachowiak A.S. Elmaghraby R. Smolikova J.M. Zurada Computer Science and Engineering Program University of Louisville Louisville KY USA Department of Computer Engineering and Computer Science University of Louisville Louisville KY USA Department of Electrical and Computer Engineering University of Louisville Louisville KY USA

ISBN: (纸本)0780370449

A neural-statistical approach to biomedical image interpolation using generalized regression neural networks is presented. These networks are basis function architectures that approximate any arbitrary function between input and output vectors directly from training samples, and with any desired degree of smoothness, and thus can be used for multidimensional interpolation. Experimental results compare favorably with other interpolation techniques. Because of their flexibility and ease of training, generalized regression networks can be used to complement existing approaches, and can be especially useful for post-registration image fusion and visualization.

关键词： Neural networks biomedical imaging Interpolation Kernel biomedical engineering Spline Computer science biomedical computing Computer networks visualization

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MRI head segmentation for object based volume visualization

MRI head segmentation for object based volume visualization

引用

Australian and New Zealand conference on Intelligent Information Systems

作者： Zou Qingsong Kwoh Chee Keong Ng Wan Sing Chen Yintao School of Computer Engineering Nanyang Technological University Singapore School of Mechanical & Production Engineering Nanyang Technological University Singapore

ISBN: (纸本)1740520610

In this paper, we present a new image segmentation approach for MRI of the head, which is a semi-automatic process. Unlike automatic segmentation or manual segmentation, the semi-automatic segmentation approach is a robust and interactive segmentation process. This approach carries out 3D volume data segmentation based on 2D image slices. By utilising the user-provided image mask, including areas of interest or structural information, the semi-automatic segmentation process can generate a new segmented volume dataset and structural information. The object based volume visualization method can use this segmented dataset and structural information to perform structure based manipulation and visualization, which cannot be achieved using a normal volume rendering method.

关键词： Magnetic resonance imaging Image segmentation Rendering (computer graphics) Head Data visualization biomedical imaging Surgery Computer displays Quantum computing Augmented reality

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4D space-time techniques: a medical imaging case study 01

4D space-time techniques: a medical imaging case study

引用

IEEE conference on visualization

作者： M. Tory N. Rober T. Moller A. Celler M.S. Atkins School Of Computing Science Simon Fraser University Canada School Of Computer Science Otto-von-Guericke University of Magdeburg Germany Nuclear Medicine Vancouver Hospital and Health Sciences Center Canada Division of Nuclear Medicine Vancouver Hospital and Health Sciences Centre School Of Computing Science Simon Fraser University

ISBN: (纸本)0780372018

We present the problem of visualizing time-varying medical data. Two medical imaging modalities are compared-MRI and dynamic SPECT. For each modality, we examine several derived scalar and vector quantities such as the change in intensity over time, the spatial gradient, and the change of the gradient over time. We compare several methods for presenting the data, including isosurfaces, direct volume rendering, and vector visualization using glyphs. These techniques may provide more information and context than methods currently used in practice; thus it is easier to discover temporal changes and abnormalities in a data set.

关键词： biomedical imaging Computer aided software engineering Data visualization Magnetic resonance imaging Medical diagnostic imaging Nuclear medicine Isosurfaces Degenerative diseases Multiple sclerosis Displays

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Easy Java programming for teaching image-processing

Easy Java programming for teaching image-processing

引用

IEEE International conference on Image Processing

作者： D. Sage M. Unser Biomedical Imaging Group Swiss Federal Institute of Technology Switzerland

We have designed a series of computer sessions build around ImageJ (a public-domain software for image analysis), as a practical complement to a two-semester course in image processing. The students are challenged with simple practical imaging problems as they acquire hands-on practice by experimenting with image-processing operators. In the process, they also learn how to program standard image-processing algorithms in Java. This is made possible thanks to a programmer-friendly environment and a software interface that greatly facilitates the developments of plug-ins for ImageJ. Since our students have generally not acquired programming skills yet (they typically do not even know Java), we use a learning-by-example teaching strategy, with good success.

关键词： Java Education Image processing biomedical imaging Application software Laboratories visualization Software algorithms biomedical computing Image analysis

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Hybrid optimization for ultrasound and multimodal image registration

Hybrid optimization for ultrasound and multimodal image regi...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： M.P. Wachowiak R. Smolikova A.S. Elmaghraby Computer Science and Engineering University of Louisville Louisville KY USA

Optimization of similarity metrics is an important component of many biomedical image registration applications that greatly affects registration outcome. Selection of an optimization approach is dependent on the modalities being registered, the characteristics of the similarity function, and available computational resources. This paper addresses optimization approaches for 2D and 3D rigid body intra- and multimodal ultrasound registration. Stochastic and direct techniques are compared for mutual information and correlation ratio functions. A new direct/stochastic hybrid approach based on the tabu search is also proposed. visualization and experimental results suggest the usefulness of such an approach. Results also show that the tabu hybrid technique compares favorably with traditional techniques, based on accuracy and number of function evaluations.

关键词： Ultrasonic imaging Image registration biomedical imaging Stochastic processes Optimization methods Simulated annealing biomedical computing Mutual information Humans Robustness

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A PDE approach for measuring tissue thickness

A PDE approach for measuring tissue thickness

引用

conference on Computer Vision and Pattern Recognition (CVPR)

作者： A. Yezzi J.L. Prince School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

ISBN: (纸本)0769512720

We outline an Eulerian framework for computing the thickness of tissues between two simply connected boundaries. Thickness is defined as the length of trajectories which follow a smooth vector field constructed in the region between the boundaries. A pair of partial differential equations (PDEs) are then solved and combined to yield length without requiring the explicit construction of the trajectories. An efficient, stable, and computationally fast solution to these PDEs is found by careful selection of finite differences according to an upwinding condition. The behavior and performance of the method is demonstrated on two simulations and two magnetic resonance imaging data sets in two and three dimensions. These experiments reveal very good performance and show strong potential for application in tissue thickness visualization and quantification.

关键词： Thickness measurement Myocardium Alzheimer's disease Image segmentation Magnetic resonance imaging Data visualization biomedical imaging Image analysis Cardiac disease Cardiovascular diseases

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Mobile computing and industrial augmented reality for real-time data access

Mobile computing and industrial augmented reality for real-t...

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International conference on Emerging Technologies and Factory Automation (ETFA)

作者： Xiang Zhang Y. Genc N. Navab Imaging and Visualization Department Siemens AG Corporate Research and Development Princeton NJ USA

ISBN: (纸本)0780372417

Augmented reality (AR) is a technology that enhances the user's view of real world with virtual objects. AR is a relatively new field and seeks applications in a wide range of areas from medicine to industry. Applying AR with mobile computing, we present a new method for information access in industrial environments. We, in this paper, present a framework that is applicable to different scenarios in larger industrial settings for spatial data access, navigation, and image augmentation in realtime. In the core of our framework lies a mobile computer equipped with a camera. The camera observes the environment for visual coded markers. These markers are registered to a global coordinate system through available drawings or floor plans. The tracker software processes images coming from the camera at moderate frame rates (typically 12fps) and estimates the location of the user. The system then can guide the user through the environment, provide the user with location relevant data from a spatial database, and augment the view of the user through the camera. Data exchange is done via a wireless network and the user interface allows the user to access various types of data without considerable effort.

关键词： Mobile computing Computer industry Augmented reality Cameras biomedical imaging Navigation Image databases Spatial databases Wireless networks User interfaces

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Modeling the respiratory motion of solitary pulmonary nodules for investigating SPECT tumor imaging

Modeling the respiratory motion of solitary pulmonary nodule...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： M.S. Smyczynski W.P. Segars M.V. Narayanan P.H. Pretorius H.C. Gifford T.H. Farncombe E.A. Hoffman B.M.W. Tsui M.A. King Division of Nuclear Medicine University of Massachusetts Medical Center Worcester MA USA Department of Biomedical Engineering North Carolina State University Chapel Hill NC USA Department of Radiology University of Iowa IA USA Department of Biomedical Engineering and the Department of Radiology North Carolina State University Chapel Hill NC USA

We have modeled the respiratory motion of solitary pulmonary nodules (SPN) based on the change of location of anatomic structures in the lungs determined from breath-held CT images of volunteers acquired at two different stages of respiration. The resulting 3D data was visualized in summed coronal, sagittal, and transaxial projections by drawing an arrow showing the direction and magnitude of motion during inspiration. The findings reveal that there is a three-dimensional component of the motion of structures within the lung and that the magnitude and direction vary based on the specific anatomic region of the lung. This information on respiratory motion within the lungs was combined with the NCAT phantom to allow the creation of source and attenuation maps for investigating the impact of respiratory motion in single photon emission computed tomographic (SPECT) imaging for SPN with Tc-99m labeled NeoTect. With the source and attenuation distribution thus defined, the SIMIND Monte Carlo program is used to produce SPECT projection images for the normal background Tc-99m NeoTect distribution and each of the tumors separately. These projections can be combined according to the desired tumor contrast and employed to investigate the impact of respiratory motion of SPN detection using human-observer localization receiver operating characteristics (LROC) studies.

关键词： Neoplasms Lungs Attenuation Computed tomography Data visualization Imaging phantoms Single photon emission computed tomography Optical computing Monte Carlo methods Motion detection

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Telementoring and teleparamedic communication platforms and robotic systems for battlefield biomedical applications

Telementoring and teleparamedic communication platforms and ...

引用

5th Battlespace Digitization conference

作者： Jannson, T Kostrzewski, A Zeltser, G Forrester, T Phys Opt Corp Torrance CA 90501 USA

ISBN: (纸本)0819436631

A new approach to C4, in the form of supercomputer-path soft communication and computing (SC2), provides enabling technology baseline for teleparamedic and telementoring communication platforms and robotic systems. In particular, this new information technology offers full-duplex 2-D and/or 3-D wireless communication and interactive telepresence, as well as remotely-controlled semi-automatic sensing, within so-called telementoring scheme, being the specific brand of telemedicine. In this paper, we discuss the SC2 capabilities, including: 20-times, higher than prior art, compression of digital multimedia data (especially including digital video) with computing power higher than that of 100 Pentiums. The further extension of SC2-technologies, combined with nearly-autonomous teleparamedic schemes, will be also discussed.

关键词： Video Telecommunications Robotics Data communications Haptic technology Surgery visualization Cameras Data centers biomedical optics

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Scanline surfacing: building separating surfaces from planar contours

Scanline surfacing: building separating surfaces from planar...

引用

IEEE conference on visualization

作者： D. Weinstein Scientific Computing and Imaging Institute School of Computing University of Utah USA

A standard way to segment medical imaging datasets is by tracing contours around regions of interest in parallel planar slices. Unfortunately, the standard methods for reconstructing three dimensional surfaces from those planar contours tend to be either complicated or not very robust. Furthermore, they fail to consistently mesh abutting structures which share portions of contours. We present a novel, straight-forward algorithm for accurately and automatically reconstructing surfaces from planar contours. Our algorithm is based on scanline rendering and separating surface extraction. By rendering the contours as distinctly colored polygons and reading back each rendered slice into a segmented volume, we reduce the complex problem of building a surface from planar contours to the much simpler problem of extracting separating surfaces from a classified volume. Our scanline surfacing algorithm robustly handles complex surface topologies such as bifurcations, embedded features and abutting surfaces.

关键词： Surface reconstruction Biological system modeling Image segmentation biomedical imaging Image reconstruction Biology computing Electrical capacitance tomography Solid modeling Magnetic resonance imaging Labeling

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