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Rigid neuroendoscope navigation system for minimally invasive surgery

Rigid neuroendoscope navigation system for minimally invasiv...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： A.M. Eldeib A. Mohamed A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

This paper describes a high precision navigation system that helps neurosurgeons identify more easily the neuroendoscope's tip location in the patient's brain that can significantly reduce the length and increase the accuracy of minimally invasive procedures. It is an image-guided neurosurgery system that provides integrated information of preoperative 3-D medical volumes, intra-operative neuroendoscope 2-D images, position information of the endoscope and surgical tools. The system's components include data acquisition, segmentation, multi-modal registration, 3-D surface and volume reconstruction, 3-D visualization, surgical simulation and integration of tracking systems. An articulated arm (digitizer) is used for automated registration of the 3-D model to the patient, then it is integrated with the system to dynamically localize surgical instruments and the patient's head in the patient's coordinate system. The visualization subsystem shows the position and orientation of the neuroendoscope's tip in the 3-D model of preoperative Magnetic Resonance (MR) volume and in the three orthogonal (sagittal, cronoal and axial) MR slices. The system's components and clinical applications are described.

关键词： Navigation Minimally invasive surgery Neurosurgery Biomedical imaging Endoscopes Data acquisition image segmentation Surface reconstruction image reconstruction Data visualization

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Microwave engineering design laboratories: C-band rail SAR and Doppler radar systems

Microwave engineering design laboratories: C-band rail SAR a...

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Antennas and Propagation Society International Symposium

作者： M.A. Jensen D.V. Arnold D.E. Crockett Microwave Earth Remote Sensing Laboratory Department of Electrical and Computer Engineering Brigham Young University Provo UT USA

National trends appear to indicate that student and faculty interest in electromagnetic principles and practices is waning. Ironically, given the current industrial emphasis on high-frequency communications, high-speed computational systems, and high-bandwidth interconnection requirements, we find ourselves in a situation where increasing numbers of engineers need to have a grasp of high-frequency fundamentals. To address this need, we have refocused the electromagnetic teaching laboratories in the electrical and computer engineering department at Brigham Young University to provide students with relevant, motivational design experiences with microwave systems. Our current laboratories are based on a 6 GHz Doppler radar in our junior-level course, and a 6 GHz synthetic aperture radar (SAR) in the senior-level course. These laboratories focus on taking students through the entire design process, beginning with system-level engineering and moving through computer-aided design, fabrication, and testing. Because the end product is a functional, useful system, students can directly see the relevance of the experience as well as the associated theory taught in the accompanying course.

关键词： Railway engineering Design engineering Laboratories Rails Communication industry computer industry Metals industry Microwave communication Education Doppler radar

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Sea ice classification using a neural network algorithm for NSCAT

Sea ice classification using a neural network algorithm for ...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Jun-Dong Park W.L. Jones J. Zec Central Florida Remote Sensing Laboratory Department of Electrical and Computer Engineering University of Central Florida Orlando FL USA

The NASA Scatterometer (NSCAT) is designed to measure wind vectors over oceans; but there are land and ice applications as well. This paper presents recent work to develop sea ice classification algorithms based on neural network technology. Multi-layer perceptron (MLP) neural networks are trained using multi-azimuth, dual-linear polarized normalized radar cross section measurements from Ku-band NSCAT. Algorithms are developed to classify the first-year sea ice edge in both the Arctic and Antarctic. For the Arctic region, after classifying the ice boundary, both first-year and multi-year classifications are made and expressed as multi-year fraction. NSCAT results are compared with corresponding ice products from the passive microwave Special Sensor Microwave imager. Results show the utility of satellite scatterometers and neural network techniques for classifying sea ice in near-real time and independently of other sensors.

关键词： Sea ice Neural networks Radar measurements Sea measurements Arctic NASA Oceans Classification algorithms Marine technology Space technology

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Normalization of NEXRAD antenna gain for overlapping radars

Normalization of NEXRAD antenna gain for overlapping radars

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Antennas and Propagation Society International Symposium

作者： S. Boustany W.L. Jones T. Kasparis Central Florida Remote Sensing Laboratory Electrical and Computer Engineering Department University of Central Florida Orlando FL USA

The NOAA National Weather Service operates a network of NEXRAD Doppler meteorological radars to measure severe weather, and precipitation is inferred from the volume scattering from hydrometeors. The NEXRAD, WSR-88D radar, is a calibrated system that measures absolute volume reflectivity (dBZ). A geophysical algorithm is used to relate rainfall intensity to the measured dBZ. The NEXRAD system comprises overlapping radars to provide nearly complete coverage over the continental US. After installation and certification, absolute radar calibration for the NEXRAD is maintained by a loop-back calibration that samples the transmitter through a known attenuation into the receiver and processor; however there is no provision to recalibrate the antenna gain and radome losses. Without an external calibration any NEXRAD may have biases that can cause significant errors in the precipitation products. The problem of combining multiple radars to provide extended coverage is not new. This paper presents an improved method that uses low-elevation radar reflectivity scans of precipitation events taken asynchronously in time. It is applied to two NEXRAD radars located in Melbourne (KMLB) and Miami (KAMX), Florida. Reflectivity data analyzed for two precipitation events indicate consistent, time-invariant dBZ biases.

关键词： Radar antennas Meteorological radar Doppler radar Geophysical measurements Reflectivity Calibration Antenna measurements Volume measurement Radar scattering Radar measurements

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POLSAR data compensation for terrain azimuth slope variation

POLSAR data compensation for terrain azimuth slope variation

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： J.S. Lee D.L. Schuler T.L. Ainsworth W.M. Boerner Remote Sensing Division Code 7263 Naval Research Laboratory Inc. Washington D.C. DC USA Department of Electrical Engineering and Computer Science University of Illinois Chicago Chicago IL USA

This paper addresses the problem of polarimetric SAR data correction for slope induced radar cross section variations in the azimuth direction. Most radiometric slope corrections remove slope effects in the range direction to account for local incidence angle variation. Two approaches to compensate azimuth slope effects are proposed. In the first approach, the DEM, obtained from interferometric SAR or other means is used to estimate the orientation angle, and in the second approach, the orientation angle is derived from Cloude's and Huynen's decompositions, and the peak-shift in polarization signature. Comparison on the accuracy of estimating the orientation angle with that derived from the DEM is given. NASA/JPL AIRSAR data is used for illustration.

关键词： Azimuth Covariance matrix Polarization Symmetric matrices Synthetic aperture radar Reflection remote sensing Laboratories Radar cross section Radiometry

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Lessons learned from full-spectral modelling of signatures of an estuary front

Lessons learned from full-spectral modelling of signatures o...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： S.R. Chubb A.L. Cooper J.C. West G.M. Nedlin Remote Sensing Division Code 7252 Naval Research Laboratory Inc. Washington D.C. DC USA School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA Department of Physics Worcester Polytechnic Institute Worcester MA USA

Previously, the authors have modeled radar signatures, involving large (/spl sim/10-15 dB) variations in radar cross-section (RCS), that have been observed at strongly convergent ocean fronts and at an estuarine front. In each of these cases, they obtained quantitative agreement with measurement but only by including wave-breaking (WB) effects in an approximate manner. However, in each case, they used the composite scattering (CS) model at a frequency, where this model may be deficient. For this reason, questions remain concerning the importance of WB effects in these simulations. In the present study, they monitor the sensitivity of the simulations with respect to this CS model approximation by comparing the results from three different radar model simulations of RCS, derived from a common wave spectrum. The spectrum is calculated using a full-spectral treatment of wave-current interaction. The resulting simulations are used to model the radar signature of the buoyant plume associated with the efflux of fresh water from the Chesapeake Bay that was observed during the COPE-2 experiment. In each case, it is possible to simulate this signature, in quantitative agreement with experiment, but only by including WB effects. However, CS model predictions for the behavior of the signature do not agree with the comparable predictions from the two remaining models. Additional simulations indicate these differences result from higher order terms that are not included in the Kirchoff approximation.

关键词： Radar cross section Sea measurements Oceans Radar scattering Frequency Predictive models remote sensing Laboratories Telephony Physics computing

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Generalized orthogonal subspace projection approach to multispectral image classification 4

Generalized orthogonal subspace projection approach to multi...

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image and Signal processing for remote sensing IV 1998

作者： Ren, Hsuan Chang, Chein-I Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States

ISBN: (纸本)9780819429599

Orthogonal subspace projection (OSP) has been successfully applied to hyperspectral image processing. In order for OSP to be effective, the number of bands must be no less than that of signatures to be classified so that there are sufficient dimensions to accommodate individual signatures to discriminate one another via orthogonal projection. This intrinsic constraint is not an issue for hyperspectral images since they generally have hundreds of bands which are more than the number of signatures resident within images. It, however, may not be true for multispectral images where the number of signatures to be classified is greater than the number of bands such as 3-band SPOT images. This paper presents a generalization of OSP, called generalized OSP (GOSP) to relax this constraint in such a fashion that OSP can be extended to multispectral image processing in an unsupervised fashion. The idea of GOSP is to create new additional band images nonlinearly from original multispectral images so as to achieve sufficient dimensionality prior to OSP classification. It is then followed by an unsupervised OSP classifier, called automatic target detection and classification algorithm (ATDCA) for classification. The effectiveness of the proposed GOSP is evaluated by a 3-band SPOT and a 4-band Landsat MSS images. The experimental results has shown that GOSP significantly improves the classification performance of OSP. © 1998 SPIE.

关键词： Landsat

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An interference rejection approach to noise adjusted principal components transform

An interference rejection approach to noise adjusted princip...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Chein-I Chang Qian Du Remote Sensing Signal and Image processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

ISBN: (纸本)0780344030

A signal-to-noise ratio based PCA approach, called maximum noise fraction (MNF) transformation or noise adjusted principal components (NAPC) transform PCA was previously developed to arrange principal components in decreasing order of image quality rather than data variance as done for PCA. One of major disadvantages of this approach is that the noise covariance matrix must be estimated accurately from the data a priori. Another is that the factor of interference is not taken into account in MNF or NAPC where the effect of interference tends to be more serious than noise in hyperspectral images. In this paper, these two problems are addressed by considering the interference as a separate unwanted signal source from which an interference rejection approach to noise adjusted principal components transform (IRNAPC) can be developed in a similar manner that the NAPC was derived. It is shown that if interference is taken care of properly, IRNAPC significantly improves NAPC. Additionally, interference annihilation also improves the estimation of the noise covariance matrix.

关键词： Signal to noise ratio Covariance matrix Principal component analysis Hyperspectral imaging Multispectral imaging Object detection Interference suppression remote sensing Signal processing image processing

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Unsupervised linear unmixing Kalman filtering approach to signature extraction and estimation for remotely sensed imagery

Unsupervised linear unmixing Kalman filtering approach to si...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： C. Brumbley Chein-I Chang Remote Sensing Signal and Image processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Linear Unmixing Kalman Filtering (LUKF) approach was recently developed which incorporates the concept of linear unmixing into Kalman filtering so as to achieve signature abundance estimation, subpixel detection and classification for remotely sensed images. However, LUKF assumes a complete knowledge of the signature matrix used in the linear mixture model. In this paper, the LUKF is extended to an unsupervised LUKF where no knowledge about the signature matrix is required a priori. The unsupervised learning method proposed for the ULUKF is derived from a vector quantization-based clustering algorithm. It employs a nearest-neighbor rule to group potential signatures resident within an image scene into a class of distinct clusters whose centers represent different types of signatures. These clusters' centers are then used as if they were true signatures in the signature matrix LUKF. In order to evaluate the effectiveness of ULUKF, HYDICE images were used for assessment. The results produced by ULUKF show that subpixel detection and classification can be performed.

关键词： Kalman filters Nonlinear filters Filtering Vector quantization Clustering algorithms Iterative algorithms State estimation remote sensing Signal processing image processing

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Sonar resolution-based environment mapping 15

Sonar resolution-based environment mapping

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15th IEEE International Conference on Robotics and Automation, ICRA 1998

作者： Cahut, Leyla Vlavanis, Kimon P. Delic, Hakan Robotics and Automation Laboratory Center for and Advanced Computer Studies University of Southwestern Louisiana LafayetteLA70504 United States Signal and Image Processing Laboratory Department of Electrical Engineering BogaziCi University Bebek 80815 Istanbul Turkey

ISBN: (纸本)078034300X

Ultrasonic range sensors are used to obtain the information required for collision-free navigation of a mobile robot in a semi-structured or unstructured environment. A set of range readings from a ring of sonars are correlated to acquire a 2D map of the robot's environment. The map is continuously enhanced via novel matching and update algorithms as new data are collected while the robot is in motion. The algorithm utilizes confidence measures that are directly obtained from the sonar's resolution or accuracy. There are no additional modeling assumptions and the approach is robust. The algorithms are experimentally tested on the Nomad 200 mobile robot and Nomad's Cognos Software Development Package. © 1998 IEEE.

关键词： Software testing

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