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Multimodality image registration and fusion using neural network

Journal of Harbin Institute of Technology(New Series) 2003年第3期10卷 235-240页

作者： Mostafa G Mostafa Aly A Farag Edward Essock Computer Vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USAComputer Vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USADept. of Psychology University of Louisville Louisville kY 40292 USA

Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.

关键词： data fusion image registration image interpolation neural network, 3-D model building

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Validating linear elastic and linear viscoelastic models of lamb liver tissue using cone-beam CT

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International Congress Series 2005年 1281卷 473-478页

作者： Shi, Hongjian Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

The purpose of this paper is to validate simple linear elastic model and linear viscoelastic models for lamb liver tissue deformation using high resolution cone-beam CT images. The resolution of the scanned images is 5 to 25 times higher than typical CT scans. The tissue deformation details in the contact region between the tissue and the indentor can be detected and rendered for smaller force loads. For these loads, it is difficult to accurately predict the volume and surface changes using typical low resolution CT scans. Surgical simulations rely on the accurate representation of the mechanical response of the soft tissues which are subject to surgical manipulations. If the simulation results using a model are quite different from reality, it can be concluded that such model is not applicable to the modelling of the targeted tissue. From simulation results we compare the deformed tissue with that obtained from experiments to verify the applicability of the model to soft tissue deformation. For our validation, fresh ex vivo lamb liver is chosen to validate the linear elastic model and the linear viscoelastic model. © 2005.

关键词： Cone-beam CT Finite element modeling Tissue deformation

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Feature extraction in image analysis

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 1997年第4期16卷 62-73页

作者： Umbaugh, SE Wei, YS Zuke, M Computer Vision and Image Processing Laboratory Southem Illinois University Edwardsville USA

images are important for many biomedical applications. Here, the authors focus on the feature-extraction part of the image analysis process. The following topics are dealt with: feature vectors and feature spaces; binary object features; histogram features; color features; spectral features; feature extraction using CVIPtools; analysis/preprocessing.

关键词： Feature extraction image analysis Robustness image color analysis Pixel Filtering Colored noise Frequency Data mining Information analysis

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Non-rigid registration techniques for automatic follow-up of lung nodules

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International Congress Series 2005年 1281卷 1115-1120页

作者： El-Baz, Ayman Yuksel, Seniha E. Elshazly, Salwa Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

Our long-term research goal is to develop an automatic approach for early detection of lung nodules that may lead to lung cancer. This paper focuses on the monitoring of the progress (growth or shrinking) of lung nodules in successive chest low dose CT (LDCT) scans of a person using non-rigid registration. The overall nodule detection approach consists of four main steps: (1) extraction of lung region by modeling the gray level distribution of LDCT slices using a linear combination of Gaussians, (2) classifying the lung region into homogenous tissues, arteries, veins and lung nodules, (3) applying rigid registration using a combination of segmentation information and mutual information as a similarity measure, and (4) compensating for the effects of heartbeats and respiration using non-rigid registration. Our earlier work addressed a number of steps in this protocol;this paper focuses on the registration step. We show that proper registration could lead to precise identification of the progress of the lung nodules. © 2005.

关键词： Lung nodules Motion compensation Mutual information Registration Segmentation

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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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2004 International Conference on image processing, ICIP 2004

作者： Farag, Aly A. Abdel-Hakim, Alaa E. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292

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. © 2004 IEEE.

关键词： image processing

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Probability density estimation by linear combinations of Gaussian kernels-generalizations and algorithmic evaluation

Probability density estimation by linear combinations of Gau...

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International Conference on Multimedia Technology

作者： Farag, Amal A. Ali, Asem M. Elhabian, Shireen Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

ISBN: (纸本)9781612847740

This paper examines parametric density estimation using a variable weighted sum of Gaussian kernels, where the weights may take positive and negative values. Various statistical properties of the estimator are studied as well as its extensions to multidimensional probability density estimation. Identification of the estimator parameters are computed by a modified EM algorithm and the number of kernels are estimated by information theoretic approach, using the Akiake Information Criterion (AIC). This paper provides empirical evaluation of the estimator with respect to window-based estimators and the classical linear combinations of Gaussian estimator that uses only positive weights, showing its robustness (in terms of accuracy and speed) for various applications in image and signal analysis and machine learning. © 2011 IEEE.

关键词： Probability density function

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Dynamic weighting of facial features for automatic pose-invariant face recognition

Dynamic weighting of facial features for automatic pose-inva...

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2012 9th Conference on computer and Robot vision, CRV 2012

作者： Mostafa, Eslam A. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

ISBN: (纸本)9780769546834

This paper proposes an automatic pose-invariant face recognition system. In our approach, we consider the texture information around the facial features to compute the similarity measure between the probe and gallery images. The weight of each facial feature is dynamically estimated based on its robustness to the pose of the captured image. An approach to extract the 9 facial features used to initialize the Active shape model is proposed. The approach is not dependent on the texture around the facial feature only but incorporates the information obtained about the facial feature relations. Our face recognition system is tested on common datasets in pose evaluation CMU-PIE and FERET. The results show out-performance of the state of the art automatic face recognition systems. © 2012 IEEE.

关键词： Face recognition

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Less is more: Cropping to improve facial recognition with thermal images

Less is more: Cropping to improve facial recognition with th...

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2nd International Conference on Multimedia Technology, ICMT 2011

作者： Gault, Travis R. Mostafa, Eslam Farag, Ahmed A. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

ISBN: (纸本)9781612847740

Numerous studies have investigated the functionality of the human facial recognition mechanisms with aims to improve computer vision methodologies. Understanding these mechanisms is important for applications in computer vision, as one goal of researchers is to create automatic facial recognition systems to equal the robustness of the human facial recognition system. Work in the field of human facial recognition shows that humans are able to recognize faces under very challenging scenarios, including partial occlusion. However, most human facial recognition experiments are conducted in the visible and near-infrared spectrums. During human facial recognition experiments with thermal images conducted in the lab, we found that removing the lower face yields better recognition results than when using the entire face. These tests included standard facial recognition algorithms and the results showed Rank 1 Recognition improvements of 10-25%, depending on the amount of occlusion derived from certain anatomical landmarks. © 2011 IEEE.

关键词： computer vision

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Cerebrovascular segmentation for MRA data using level sets

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International Congress Series 2003年第C期1256卷 246-252页

作者： Hassan, Hossam Farag, Aly A Computer Vision Image Processing Laboratory University of Louisville Lutz Hall Louisville KY 40292 United States

In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Phase Contrast Magnetic Resonance Angiography, “PCMRA”. Classification model finds an optimal partition of homogeneous classes with regular interfaces. Regions and their interfaces are represented by level set functions. The algorithm initializes level sets in each image slice using automatic seed initialization and then iteratively, each level set approaches the steady state and contains the vessel or non-vessel area. The results are validated using a phantom that simulates the “PCMRA”. The approach is fast and accurate. Results on various cases demonstrate the accuracy of the approach. © 2003, Elsevier Science B.V. All rights reserved.

关键词： Level set segmentation PCMRA PDE Seed initialization Vascular tree

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Statistical morphable model for human teeth restoration

Statistical morphable model for human teeth restoration

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作者： Mostafa, Eslam Elhabian, Shireen Abdelrahim, Aly Elshazly, Salwa Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville KY United States

ISBN: (纸本)9781479957514

While traditional dental fillings are molded during a dental visit, dental restoration (e.g. inlays and onlays) are fabricated in a dental lab to offer a long lasting reparative solution to tooth decay or similar structural damage. Such process requires dental technicians who are highly trained experts in tooth anatomy to pick an appropriate standard tooth model from a tooth database. The success of a restoration process primarily relies on the acquisition and modeling of an accurate 3D shape of the occlusal surface of interest for manufacturing purposes. Based on a single optical image, this paper provides an economical and automated solution for tooth restoration where user intervention is kept at the minimal. The inherit relation between the photometric information and the underlying 3D shape is formulated as a coupled statistical model where the effect of illumination is modeled using Spherical Harmonics. Moreover, shape and texture alignment is accomplished using a proposed definition of anatomical jaw landmarks which are automatically detected. The system is evaluated on database of 32 jaws for crown, inlay, and onlay restoration. Results shows a promising performance for using the proposed approach in clinical application. © 2014 IEEE.

关键词： Restoration

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