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Intensity and region-of-interest-based finite-element modeling of brain deformation

International Congress Series 2004年第C期1268卷 373-377页

作者： Shi, Hongjian Farag, Aly Computer Vision Image Processing Laboratory Electrical Computer Engineering University of Louisville Louisville KY 40292 403 Lutz Hall Building United States

This paper proposes intensity and region-of-interest-based finite-element modeling of brain deformation. The modeling is based on the intensities of voxels within each element and motion analysis of region of interest (ROI) for image-guided minimally invasive surgery (MIS) applications. It is proposed to configure an ROI at the tip of surgical tools instead of the whole brain, so that the FEM is applied only on the ROI, and the maximum nodal displacement outside the ROI is small and in control. The deformed MR image using the proposed finite-element modeling shows better proportion to its original structures. © 2004, Elsevier Science B.V. All rights reserved.

关键词： Brain deformation Finite-element modeling Minimal invasive surgery

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image content-based active sensor planning for a mobile trinocular active vision system

Image content-based active sensor planning for a mobile trin...

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IEEE International Conference on image processing

作者： A.A. Farag A.E. Abdel-Hakim Computer Vision and Image Processing Laboratory University of Louisville Louisville KY

In this paper, we present a sensor planning approach for a mobile trinocular active vision system. At the stationary state (i.e., no motion) the sensor planning system calculates the generalized cameras' parameters (i.e., translational distance from the center, zoom, focus and vergence) using deterministic geometric specifications of both the sensors and the objects in their field of view. Some of these geometric parameters are difficult to be predetermined for the mobile system operation. In this paper, a new sensor planning approach, based on processing the content of the captured images, is proposed. The approach uses a combination of a closed-form solution for the translation between the three cameras, the vergence angle of the cameras as well as zoom and focus settings with the results of the correspondences between the acquired images and a predefined target object(s) obtained using the SIFT algorithm. We demonstrate the accuracy of the new approach using practical experiments.

关键词： image sensors Sensor systems Machine vision Cameras Focusing image reconstruction Robot sensing systems Robot vision systems Object detection Process planning

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Detecting regional abnormal cardiac contraction in short-axis MR images using independent component analysis

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7th International Conference on Medical Imaging and computer Assisted Intervention, MICCAI 2004

作者： Suinesiaputra, A. Üzümcü, M. Frangi, A.F. Kaandorp, T. Reiber, J. Lelieveldt, B. Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Computer Vision Group Aragon Institute of Engineering University of Zaragoza Zaragoza Spain

ISBN: (纸本)3540229760

Regional myocardial motion analysis is used in clinical routine to inspect cardiac contraction in myocardial diseases such as infarction or hypertrophy. Physicians/radiologists can recognize abnormal cardiac motion because they have knowledge about normal heart contraction. This paper explores the potential of Independent Component Analysis (ICA) to extract local myocardial contractility patterns and to use them for the automatic detection of regional abnormalities. A qualitative evaluation was performed using 42 healthy volunteers to train the ICA model and 6 infarct patients to test the detection and localization. This experiment shows that the evaluation results correlate very well to the clinical gold standard: delayed-enhancement MR images. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Independent component analysis

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A Unified Framework for Performance Evaluation of 3-D Reconstruction Techniques

A Unified Framework for Performance Evaluation of 3-D Recons...

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

作者： A. Eid A. Farag Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY USA

In this paper we consider the problem of performance evaluation of 3-D reconstruction techniques from calibrated sequence of images. We propose a unified framework for the evaluation process assuming the existence of ground truth data collected by a 3-D laser scanner. Firstly, we propose a new pre-evaluation technique for 3-D data registration based on silhouettes alignment. The performance of this technique is independent of the output quality of the 3-D reconstruction technique under test. This is a major advantage of our technique since the quality issue, which is not guarantee under the evaluation topic, is a challenge for any 3-D registration technique. Secondly, we propose a geometrically based evaluation methodology. The method is based on the geometrical matching of uniformly distributed patches of both ground truth and under-test data sets. The method is insensitive to the relative density of data sets. In addition, it provides a method for localizing errors which is a crucial step for diagnosis and data fusion post-evaluation techniques. Finally, we provide experimental results on the evaluation of stereo and space carving techniques.

关键词： Three dimensional displays Stereo vision Testing computer vision Optical sensors Cameras image processing Laboratories Stereo image processing Fuses

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Real-time vision-based approach for probe tracking in operating room

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International Congress Series 2004年 1268卷 467-472页

作者： Aly A. Farag M.Sabry Hassouna Ayman El-Baz S. Hushek Computer Vision and Image Processing Laboratory Electrical and Computer Engineering University of Louisville 403 Lutz Hall Bldg. Louisville KY 40292 USA Department of Neurological Surgery University of Louisville USA

A hand-held surgical probe is an essential component of any image-guided neurosurgery (IGNS). During the surgical procedure, the IGNS tracks the probe position and displays the anatomy beneath it as three orthogonal image slices on a workstation-based 3D imaging system. Existing IGNS systems use different tracking techniques including mechanical, optical, ultrasonic, and electromagnetic systems. In this paper, we present a new computational vision-based probe tracking technique, which provides both position and orientation. We also propose another new computational vision-based technique to track the patient head and thus compensate for its movement during probing procedure. The proposed system is completely passive, its stereo cameras detect the presence of the probe using available visible light, and reports on their exact location and orientation in patient physical space in real time. We have validated the system using a skull phantom and a hand made probe.

关键词： image-guided neurosurgery Head motion tracking Probe tracking vision tracking

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Automatic detection and recognition of lung abnormalities in helical CT images using deformable templates

Automatic detection and recognition of lung abnormalities in...

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Medical image Computing and computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings

作者： Farag, Aly El-Baz, Ayman Gimel'Farb, Georgy G. Falk, Robert Hushek, Stephen G. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Department of Computer Science Tamaki Campus University of Auckland Auckland New Zealand Medical Imaging Division Jewish Hospital Louisville KY United States iMRI Department Norton Hospital Louisville KY United States

ISBN: (纸本)3540229779

Automatic detection of lung nodules is an important problem in computer analysis of chest radiographs. In this paper we propose a novel algorithm for isolating lung nodules from spiral CT scans. The proposed algorithm is based on using four different types of deformable templates describing typical geometry and gray level distribution of lung nodules. These four types are (z) solid spherical model of large-size calcified and non-calcified nodules appearing in several successive slices;(ii) hollow spherical model of large lung cavity nodules;(Hi) circular model of small nodules appearing in only a single slice;and (iv) semicircular model of lung wall nodules. Each template has a specific gray level pattern which is analytically estimated in order to fit the available empirical data. The detection combines the normalized cross-correlation template matching by genetic optimization and Bayesian post-classification. This approach allows for isolating abnormalities which spread over several adjacent CT slices. Experiments with 200 patients' CT scans show that the developed techniques detect lung nodules more accurately than other known algorithms. © Springer-Verlag Berlin Heidelberg 2004.

关键词： computer vision

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Object recognition using local information content

Object recognition using local information content

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International Conference on Pattern Recognition

作者： G. Fritz L. Paletta H. Bischof Joanneum Research Institute of Digital Image Processing Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Graz Austria

Object identification from local information has recently been investigated with respect to its potential for robust recognition, e.g., in case of partial object occlusions, scale variation, noise, and background clutter in detection tasks. This work contributes to this research by a thorough analysis of the discriminative power of local appearance patterns and by proposing to exploit local information content for object representation and recognition. In a first processing stage, we localize discriminative regions in the object views from a posterior entropy measure, and then derive object models from selected discriminative local patterns. Object recognition is then applied to test patterns with associated low entropy using an efficient voting process. The method is evaluated by various degrees of partial occlusion and Gaussian image noise, resulting in highly robust recognition even in the presence of severe occlusion effects.

关键词： Object recognition Noise robustness Entropy Background noise Object detection Information analysis Pattern analysis Pattern recognition Testing Voting

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Enhancement of stents using interference of low-frequency ultrasonic echo signals

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Journal of Medical Ultrasonics 2004年第2期31卷 67-73页

作者： Ohashi, Gosuke Ohya, Akihisa Tobise, Kazimobu Akiyama, Iwaki Faculty of Engineering Shizuoka University Hamamatsu Japan Institute of Information Sciences and Electronics University of Tsukuba Tsukuba Japan Shoryo Electronic Corporation Kamakura Japan Faculty of Engineering Shonan Institute of Technology Fujisawa Japan Image Processing and Vision Research Laboratory Department of Electrical and Computer Engineering University of California at Santa Barbara Santa Barbara CA 93106-9560 United States

Purpose. We set out to enhance the imaging of stents used for coronary coarctation surgery without imaging the reticulation of the stent. Because the stent is a reticulated structure, there is a relation between ultrasound wavelength and the interstice reticulation that produces the echo. Methods. First we performed computer simulation by ultrasound frequency of transmitted signals to analyze this relation. Then, instead of controlling the transmitted wave, we processed the returned signals through a band-pass filter because of the difficulty of controlling the transmitted waves of diagnostic ultrasound equipment. Following this, we conducted experiments on an agar gel phantom containing a stent to verify the effectiveness of this method. Results. The simulation confirmed that the stent was apparent when the ultrasonic wavelength equaled the product of an integer and twice the interval of the reticulation of the stent. Application of a band-pass filter of 0.8 to 1.5MHz to the waveform returned from the agar gel phantom containing the stent. Conclusions. The effectiveness of this method in depicting the stent was confirmed. © The Japan Society of Ultrasonics in Medicine 2004.

关键词： Interference Received waveform Signal processing Stent Ultrasonic echography

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Robust occupancy detection from stereo images

Robust occupancy detection from stereo images

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International Conference on Intelligent Transportation

作者： B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA

Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.

关键词： Robustness Magnetic heads Vehicle crash testing Sensor systems Stereo vision Layout Statistical analysis Support vector machines Support vector machine classification Vehicle detection

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Building and registering parameterized 3D models of vessel trees for visualization during intervention

Building and registering parameterized 3D models of vessel t...

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International Conference on Pattern Recognition

作者： G. Langs P. Radeva D. Rotger F. Carreras Insitute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria Computer Vision Center Universitat Autònoma de Barcelona Bellaterra Spain Hospital St. Pau Barcelona Spain

In this paper, we address the problem of multimodal registration of coronary vessels by developing a 3D parametrical model of vessel trees from computer tomography data and registering it to angiography images during intervention. Thus, the interventionist takes profit from 3D data otherwise only available before the intervention. This facilitates orientation in ambiguous radiographs, interactive visualization of all vessel structures to estimate their mutual position and navigation within the vessel system and ultimately reduces the radiation the patient and the physicians are exposed to. The model is build by exploring the branching vessel tree starting from a single position and successively expanding through the vessels guided by a local deformable surface. The result is a tree of cylindrical segments each adapted to the vessel walls that is registered to angiography images in a fast and robust way. Validation on 8 patients confirms the robustness of our method.

关键词： X-ray imaging Computed tomography Robustness Angiography image segmentation image reconstruction Distortion measurement Tree graphs Data visualization Radio navigation

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