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Multi-modal medical volumes fusion by surface matching

Multi-modal medical volumes fusion by surface matching

引用

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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A robust 3-D reconstruction system for human jaw modeling 2nd

A robust 3-D reconstruction system for human jaw modeling

引用

2nd International Conference on Medical image Computing and computer-Assisted Intervention, MICCAI 1999

作者： Yamany, Sameh M. Farag, Aly A. Tasman, David Farman, Allan G. Computer Vision and Image Processing Laboratory University of Louisville United States School of Dentistry Univeristy of Louisville LouisvilleKY40292 United States

ISBN: (纸本)354066503X

This paper presents a model-based vision system for dentistry that will assist in diagnosis, treatment planning and surgical simulation. Dentistry requires the accurate 3-D representation of the teeth and jaws for diagnostic and treatment purposes. The proposed integrated computer vision system reconstructs a 3-D model of the patient’s dental occlusion using an intra-oral video camera. A modified shape from shading (SFS) technique, using perspective projection and camera calibration, extracts the 3-D information from a sequence of 2-D images of the jaw. Data fusion and 3-D registration techniques develop the complete jaw model. Triangulization is then performed, and a solid 3-D model is obtained via rapid prototyping. The system performance is investigated using ground truth data, and the results show sub-millimeter reconstruction accuracy. The system is shown to be robust in terms of speed and accuracy compared to current practices. © Springer-Verlag Berlin Heidelberg 1999.

关键词： image reconstruction

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Integrating stereo and shape from shading

Integrating stereo and shape from shading

引用

IEEE International Conference on image processing

作者： M.G.-H. Mostafa S.M. Yamany A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper presents a new method for integrating different low level vision modules, stereo and shape from shading, in order to improve the 3D reconstruction of visible surfaces of objects from intensity images. The integration process is based on correcting the 3D visible surface obtained from shape from shading using the sparse depth measurements from the stereo module by fitting a surface into the difference between the two data sets. A feedforward neural network is used to fit a surface to the error difference. An extended Kalman filter algorithm is used for the network learning. It is found that the integration of sparse depth measurements has greatly enhanced the 3D visible surface obtained from shape from shading in terms of metric measurements.

关键词： Surface fitting Shape measurement image reconstruction Layout Stereo image processing Stereo vision Surface reconstruction Neural networks Feedforward neural networks Machine vision

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A neural approach for single- and multi-image camera calibration

A neural approach for single- and multi-image camera calibra...

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IEEE International Conference on image processing

作者： M. Ahmed E. Hemayed A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper presents the neurocalibration approach as a new neural-based solution for the problem of camera calibration. Unlike some existing neural approaches, our calibrating network can match the perspective-projection-transformation matrix between the world 3D points and the corresponding 2D image pixels. Starting from random initial weights, the net can specify the camera model parameters satisfying the orthogonality constraints on the rotational transformation. In order to improve the accuracy of calibration results, the paper demonstrates the application of the neurocalibration technique to multi-image camera calibration. In such a case, many images are taken by the same camera but from different (rotated and/or translated) positions. Experiments have shown the accuracy and the efficiency of our neurocalibration technique.

关键词： Cameras Calibration Matrix decomposition Neural networks computer vision image processing Laboratories Pixel Parameter estimation Measurement errors

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Free-form surface registration using surface signatures

Free-form surface registration using surface signatures

引用

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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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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Modified fuzzy c-mean in medical image segmentation

Modified fuzzy c-mean in medical image segmentation

引用

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

作者： N.A. Mohamed M.N. Ahmed A. Farag E.E. Department Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper describes the application of fuzzy set theory in medical imaging, namely the segmentation of brain images. We propose a fully automatic technique to obtain image clusters. A modified fuzzy c-mean (FCM) classification algorithm is used to provide a fuzzy partition. Our new method, inspired from the Markov random field (MRF), is less sensitive to noise as it filters the image while clustering it, and the filter parameters are enhanced in each iteration by the clustering process. We applied the new method on a noisy CT scan and on a single channel MRI scan. We recommend using a methodology of over segmentation to the textured MRI scan and a user guided-interface to obtain the final clusters. One of the applications of this technique is TBI recovery prediction in which it is important to consider the partial volume. It is shown that the system stabilizes after a number of iterations with the membership value of the region contours reflecting the partial volume value. The final stage of the process is devoted to decision making or the defuzzification process.

关键词： Biomedical imaging image segmentation Filters Magnetic resonance imaging Fuzzy set theory Brain Classification algorithms Clustering algorithms Partitioning algorithms Markov random fields

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Object recognition using neural networks and surface signatures

Object recognition using neural networks and surface signatu...

引用

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 ...

引用

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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