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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

引用

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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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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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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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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Object recognition using neural networks and surface signatures

Object recognition using neural networks and surface signatu...

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International Joint Conference on Neural Networks (IJCNN)

作者： S.M. Yamany A.M. El-Bialy A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Systems and Biomedical Engineering Department Cairo University Egypt

We present a concept for 3D free-form object recognition using a surface representation scheme. This representation scheme captures the 3D curvature information of any free-form surface and encodes it into a 2D image corresponding to a certain point on the surface. This image is unique for this point and is independent from the object translation or orientation in space. For this reason we called this image the surface point signature (SPS). Using specially designed neural networks; the SPS images are used in the matching and recognition of 3D objects in a 3D scanned scene.

关键词： Object recognition Neural networks Layout image recognition Shape image processing Laboratories computer vision Robot vision systems Application software

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Free-form object recognition and registration using surface signatures

Free-form object recognition and registration using surface ...

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IEEE International Conference on image processing

作者： S.M. Yamany A.A. Farag A. El-Bialy Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Systems and Biomedical Engineering Department Cairo University Cairo Egypt

This paper presents a new concept for 3-D free-form surface registration and object recognition using a new surface representation scheme. This representation scheme captures the 3-D curvature information of any free-form surface and encodes it into a 2-D image corresponding to a certain point on the surface. This image is unique for this point and is independent from the object translation or orientation in space. For this reason we called this image “Surface Point Signature” (SPS). This scheme can be used as a global representation of the surface as well as a local one and also in a scale independent surface matching. It performs faster registration than existing registration approaches. We applied this technique in object registration, multimodal medical image registration and the recognition of multiple objects in a 3-D scene.

关键词： Object recognition Biomedical imaging image recognition Layout Shape image processing Laboratories image registration Robot vision systems Contracts

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Novel surface registration using the grid closest point (GCP) transform

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IEEE International Conference on image processing

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

ISBN: (纸本)0818688211

A novel approach has been developed for fast registration of two sets of 3-D curves or surfaces. The technique is an extension of Besl and Mackay's (1992) iterative closest point (ICP) algorithm. This technique solves the computational complexity associated with the ICP algorithm by applying a novel grid closest point (GCP) transform and a genetic algorithm to minimize the cost function. A detailed description of the algorithm is presented along with a comparison of its performance versus several registration techniques. Two applications are presented in this paper. In the first, the algorithm is used to register 2-D head contours extracted from CT/MRI data to correct for possible mis-alignment caused by motion artifacts during scanning. In the second, the algorithm is used to register 3-D segments of the human jaw obtained using the shape from shading technique. Registration using the GCP/GA technique is found to be significantly faster and of comparable accuracy than two popular techniques in the computer vision and medical imaging literature.

关键词： Iterative algorithms Iterative closest point algorithm Computational complexity Genetic algorithms Cost function Head Data mining Computed tomography Magnetic resonance imaging Registers

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A system for human jaw modeling using intra-oral images

A system for human jaw modeling using intra-oral images

引用

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

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

A novel integrated system is developed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video camera. A modified Shape from Shading (SFS) technique using perspective projection and camera calibration is then used to extract accurate 3D information from a sequence of 2D images of the jaw. A novel technique for 3D data registration using Grid Closest Point (GCP) transform and genetic algorithms (GA) is used to register the output of the SFS stage. Triangulization is then performed, and a solid 3D model is obtained via a rapid prototype machine. The overall purpose of this research is to develop a model-based vision system for orthodontics that will replace traditional approaches and can be used in diagnosis, treatment planning, surgical simulation and implant purposes.

关键词： Humans Cameras computer vision Data acquisition Shape Calibration Data mining Genetic algorithms Solid modeling Prototypes

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