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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Moumen Taha El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Dept. Assiut University Assiut Egypt Computer Vision and Image Processing Lab. University of Louisville Louisville KY

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement in one form or another,we present an approach to distortion calibration based on the robust the-least-median-of-squares (LMedS) estimator. Our approach is thus able to proceed in a ful ly-automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3D linear segments. Our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. Moreover we propose a method for distortion model selection based on geometrical *** experiments to evaluate the performance of this approach on synthetic and real data are reported.

关键词： Nonlinear distortion Calibration Robustness Lenses Cameras image edge detection Distortion measurement

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Video reconstructions in dentistry

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Orthodontics and Craniofacial Research 2003年第SUPPL1期6卷 108-116页

作者： Farag, A.A. Eid, A. Electrical and computer Engineering Department University of Louisville Computer Vision and Image Processing Laboratory Louisville KY 40292 United States

Objectives: To present two practical techniques for threedimensional (3D) modeling of the human jaw from a sequence of intra-oral images. Design: A data acquisition system consists of: 3D digitizing arm, CCD camera and a laser projector in addition to a software module of two 3D modeling techniques;shape from shading (SFS) and space carving (SC). Setting and sample population - Several experiments have been conducted on a sample of students at the computer vision and image processing (CVIP) Laboratory at the University of Louisville, Louisville, KY. Other experiments were performed on solid models of human jaw. Experimental variable: The SFS technique, using perspective projection and camera calibration, extracts the 3D information from a sequence of two-dimensional images of the jaw. Data fusion of range data and 3D registration techniques develop the complete jaw model. The SC approach is implemented on a sequence of calibrated images. On the two reconstructions, we fit a mesh model to the data, in order to create a solid 3D model. Outcome measure: The accuracy of the reconstructed 3D model of human jaw is calculated based on the measurements on real jaws. Results: The SFS-based technique seems to provide more faithful information about the shape of the tooth tops. However, the SC algorithm successfully reconstructed 3D models of the human jaw with sub-millimeter accuracy, which is as accurate as (or even better than) the first technique without using any range measurements or laser projectors. The average error in distance calculation was found to be 0.74 mm, which is an acceptable resolution for many orthodontics and maxillofacial applications. Conclusion: Accurate 3D reconstruction of the human jaw enables many orthodontics and dental imaging researchfindings to be applied directly to a digital jaw model - not to a cast - using computer vision and medical imaging tools. © 2003 Blackwell Munksgaard.

关键词： Data fusion Jaw modeling Registration Shape from shading Space carving

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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3rd International Conference on Information Fusion, FUSION 2000

作者： Mostafa, Mostafa G. Farag, Aly A. Essock, Edward Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY 40292 United States Department of Psychology University of Louisville Louisville KY 40292 United States

ISBN: (纸本)2725700000

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results. © 2000 Int. Soc. Inf. Fusion.

关键词： image fusion

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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International Conference on Information Fusion

作者： M.G. Mostafa A.A. Farag E. Essock Department of Electrical and Computer Engineering Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychology University of Louisville Louisville KY USA

关键词： image registration Neural networks Hyperspectral sensors Remote sensing image reconstruction Geometry Remote monitoring Intelligent sensors Satellites Laser radar

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Multi-modal medical volumes fusion by surface matching

Multi-modal medical volumes fusion by surface matching

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5th International Symposium on Signal processing and Its Applications, ISSPA 1999

作者： Eldeib, Ayman M. Yamany, Sameh M. Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville Department of Electrical Engineering Louisville KY 40292 United States

ISBN: (纸本)1864354518

Presents a fast, six degrees of freedom, registration technique to accurately locate the position and orientation of medical volumes (e.g. CT, MRI) with respect to each other for the same patient. The technique uses surface registration and maximization of mutual information. We have developed a novel technique for surface registration which produces highly accurate results when registering two different volumes of the same individual generated from the same modality, such as preoperative MR and intraoperative MR volumes. In case surface registration is not able to accurately register the different volumes, the result is enhanced by multi-modal volume registration. The gain of this combination is to have an accurate alignment and to reduce time needed for registration. For the multi-modal volume registration, the maximization of mutual information (MI) as a matching criterion is used based on genetic algorithms (GA) as a search engine. Our results demonstrate that our registration technique allows for fast, accurate, robust and completely automatic registration of multimodality medical volumes. © 1999 IEEE.

关键词： Genetic algorithms

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Free-form surface registration using surface signatures

Free-form surface registration using surface signatures

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International Conference on computer vision (ICCV)

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

The paper introduces a new free-form surface representation scheme for the purpose of fast and accurate registration and matching. Accurate registration of surfaces is a common task in computer vision. The proposed representation scheme captures the surface curvature information seen from certain points and produces images called surface signatures at these points. Matching signatures of different surfaces enables the recovery of the transformation parameters between these surfaces. We propose to use template matching to compare the signature images. To enable partial matching, another criterion, the overlap ratio, is used. This representation scheme can be used as a global representation of the surface as well as a local one and performs near real time registration. We show that the signature representation can be used to match objects in 3D scenes in the presence of clutter and occlusion. Applications presented include free-form object matching, multimodal medical volume registration and dental teeth reconstruction from intra-oral images.

关键词： Shape computer vision Surface reconstruction Application software Biomedical imaging image processing Layout Dentistry Teeth image reconstruction

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Multi-modal medical volumes fusion by surface matching

Multi-modal medical volumes fusion by surface matching

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International Symposium on Signal processing and Its Applications (ISSPA)

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

关键词： Biomedical imaging Medical diagnostic imaging Computed tomography Mutual information Magnetic resonance imaging Data mining Magnetic resonance Genetic algorithms Shape computer vision

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Using active contours and Fourier descriptors for motion tracking with applications in MRI

Using active contours and Fourier descriptors for motion tra...

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IEEE International Conference on image processing

作者： D.L. Guidry A.A. Farag Computer Vision and Image Processing Lab Electrical Engineering Department University of Louisville Louisville KY USA

To estimate motion, the edges of a moving object can be detected using active contours. After detecting the edges throughout the duration of the motion, the contours are registered together in order to obtain the motion model parameters. This idea can be applied to motion artifacts in Magnetic Resonance images (MRI) which are caused by patient motion during the acquisition of an MRI. Thus, if the patient motion can be determined, it will be possible to correct for the motion in the images. The proposed method eliminates motion artifacts by dividing the acquired MRI data into several subbands. These subbands create invariant tissue feature maps called subband images. Using active contours, the edges of each subband image are detected and the relative motion is analyzed across the different subband images, thus determining the motion parameters. From these motion parameters it is possible to correct the subband images, thus correcting the k-space yielding clear, noise-free MR images.

关键词： Active contours Tracking image edge detection Motion detection Magnetic resonance imaging Motion analysis Motion estimation Object detection Magnetic resonance image analysis

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Active contours: an overview with applications to motion artifact cancellation in MRI

Active contours: an overview with applications to motion art...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： D.L. Guidry A.A. Farag Computer Vision and Image Processing Lab Electrical Engineering Department University of Louisville Louisville KY USA

Motion can be estimated by detecting the edges of a moving object using active contours, and registering them together to obtain the motion model parameters. This idea can be applied to patient motion during the acquisition of an MRI to eliminate motion artifacts in the image. The data obtained during the MRI acquisition, the k-space, can be divided into several subbands such that each subband is acquired in a small fraction of the full imaging time. These subbands create invariant tissue feature maps called subband images. Using active contours, the relative motion is analyzed across the different subband images to determine the motion parameters. Using these motion parameters it is possible to correct the subbands, thus correcting the k-space. This has the potential to yield clear, noise-free MR images.

关键词： Active contours Magnetic resonance imaging image edge detection computer vision Motion estimation Object detection Motion detection Motion analysis Gray-scale Application software

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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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