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检索条件"机构=Computer Vision and Image Analysis Laboratory Department of Electrical Engineering"

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

引用

International Conference on Information Fusion

作者： Nima Tajbakhsh Babak N. Araabi Hamid Soltanianzadeh Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Iris Feature extraction Discrete cosine transforms image recognition Databases Training Humans

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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system computer vision Motion detection

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Constrained optimization of nonparametric entropy-based segmentation of brain structures

Constrained optimization of nonparametric entropy-based segm...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi Asl Hamid Soltanian-Zadeh School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

We propose a constrained, three-dimensional, nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capture structural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function, which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, constraints are used to improve segmentation quality. These constraints are extracted from training data. Sample results are given for the segmentation of caudate, hippocampus, and putamen, illustrating highly superior performance of the proposed method compared to the most similar methods in the literature.

关键词： Constraint optimization Brain Iterative algorithms image segmentation Shape Couplings Magnetic resonance Magnetic resonance imaging Principal component analysis Buildings

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Flagellar swimming for medical micro robots: Theory, experiments and application

Flagellar swimming for medical micro robots: Theory, experim...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Gabor Kosa Peter Jakab Nobuhiko Hata Ferenc Jolesz Zipi Neubach Moshe Shoham Menashe Zaaroor Gabor Szekely Computer Vision Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Switzerland Harvard Medical School Boston MA USA Division of MRI and Image Guided Therapy Program at Department of Radiology Brigham and Women's Hospital Boston MA USA Faculty of Mechanical Engineering Technion-Israel Institute of Technology Haifa Israel Department of Neurosurgery Rambam Medical Center Haifa Israel

Flagellar swimming is one of the swimming methods used by micro-organisms to advance in aquatic environment. The undulating motion of the flagella was successfully imitated to create propulsion for a medical swimming micro robot. The influence of a head section on the performance of such a robot is shown analytically. Swimming experiments demonstrate forward and backward swimming of a novel magnetically driven swimming tail. We intend to use the flagellar swimming tail in a three tail configuration for neurosurgical intervention in the ventricular system.

关键词： Medical robotics Tail Medical diagnostic imaging Propulsion Magnetosphere Neurosurgery Intestines computer vision Laboratories Information technology

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Using a patient image archive to diagnose retinopathy

Using a patient image archive to diagnose retinopathy

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

作者： Kenneth W. Tobin Michael D. Abramoff Edward Chaum Luca Giancardo V. Priya Govindasamy Thomas P. Karnowski Matthew T.S. Tennant Stephen Swainson Image Science and Machine Vision Group Oak Ridge National Laboratory Oak Ridge TN USA Department of Electrical and Computer Engineering University of Iowa Iowa IA USA Department of Ophthalmology and Visual Sciences University of Iowa Hospitals and Clinics Iowa IA USA Tennessee Health Science Center Hamilton Eye Institute Memphis TN USA Oak Ridge National Laboratory Oak Ridge TN USA Department of Ophthalmology University of Alberta Edmonton Canada Faculty of Medicine University of Alberta AB Canada

Diabetes has become an epidemic that is expected to impact 365 Million people worldwide by 2025. Consequently, diabetic retinopathy is the leading cause of blindness in the industrialized world today. If detected early, treatments can preserve vision and significantly reduce debilitating blindness. Through this research we are developing and testing a method for automating the diagnosis of retinopathy in a screening environment using a patient archive and digital fundus imagery. We present an overview of our content-based image retrieval (CBIR) approach and provide performance results for a dataset of 98 images from a study in Canada when compared to an archive of 1,355 patients from a study in the Netherlands. An aggregate performance of 89% correct diagnosis is achieved, demonstrating the potential of automated, web-based diagnosis for a broad range of imagery collected under different conditions and with different cameras.

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A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING VECTOR MAPS

A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING ...

引用

IEEE International Symposium on Biomedical Imaging

作者： Hossam E. Abd El Munim Aly A. Farag Computer Vision and Image Processing (CVIP) Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA

ISBN: (纸本)1424406714

In this paper, we introduce a novel global image registration approach using vector distance functions (VDF's). Edges of the source and target objects are used to represent their images. The VDF's of these edges are calculated as an implicit representation of these boundaries. An energy is formulated to measure the differences of these vectors. A variational formulation is considered to estimate the transformation parameters. Promising results in 2D and 3D are demonstrated to show the efficiency of the proposed algorithm.

关键词： Biomedical imaging image edge detection image registration Parameter estimation computer vision Mutual information Data mining Shape image processing Energy measurement

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FAST MOTION IMAGING USING REDUCED FIELD OF VIEW PARTIAL FOURIER MRI

FAST MOTION IMAGING USING REDUCED FIELD OF VIEW PARTIAL FOUR...

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IEEE International Symposium on Biomedical Imaging

作者： Harsh K. Agarwal Khaled Z. Abd-elmoniem Jerry L. Prince Image Analysis and Communication Laboratory Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

Fast MR imaging techniques often exploit the redundancy present in an underlying MR image time series to compensate for k-space undersampling. When imaging motion using techniques like HARP, DENSE, and phase contrast (PC), it is the phase in static regions that is constant and therefore redundant. In this paper, we present a technique that first estimates the phase in the static portion of an undersampled MR image time series and then uses a partial Fourier reconstruction technique to combine phase in the static portion and undersampled data to reconstruct the full image time series. The technique is illustrated using a computational phantom undergoing simulated cardiac motion and imaged using the HARP protocol. Results demonstrate a gradual degradation of accuracy with loss of data due to undersampling, indicating that a 25% speedup in imaging time is possible for an image time series in which 50% of the pixels correspond to the object that do not move over time.

关键词： Magnetic resonance imaging image reconstruction Phase estimation Protocols Frequency estimation Motion analysis image motion analysis Laboratories Imaging phantoms Computational modeling

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A Geometry-Based Local Descriptor for Range Data

A Geometry-Based Local Descriptor for Range Data

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Fredrik Viksten Klas Nordberg Image Coding Group Department of Electrical Engineering Linköping university Sweden Computer Vision Laboratory Department of Electrical Engineering Linköping university Sweden

ISBN: (纸本)9781424431618;9780769530673

We present a novel local descriptor for range data that can describe one or more planes or lines in a local region. It is possible to recover the geometry of the described local region and extract the size, position and orientation of each local plane or line-like structure from the descriptor. This gives the descriptor a property that other popular local descriptors for range data, such as spin images or point signatures, does not have. The estimation of the descriptor is dependant on estimation of surface normals but does not depend on the specific normal estimation method used. It is shown that is possible to extract how many planar surface regions the descriptor represents and that this could be used as a point-of-interest detector.

关键词： Tensile stress Layout computer vision Geometry Data mining Digital images computer applications Application software image coding Laboratories

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RECOVERY LIMITATIONS OF MEG SOURCE LOCALIZATION MODEL FOR EPILEPSY

RECOVERY LIMITATIONS OF MEG SOURCE LOCALIZATION MODEL FOR EP...

引用

IEEE International Symposium on Biomedical Imaging

作者： Mostafa Ghannad-Rezaie Kourosh Jafari-Khouzani Hamid Soltanian-Zadeh Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Department of Electrical and Computer Engineering Wayne State University Detroit MI USA

ISBN: (纸本)9781424406715;1424406714

Source localization in magnetoencephalography (MEG) has received a lot of attention in the recent years. MEG inverse problem is an ill-posed problem in from of B ntimesl =G ntimesm J mtimesl , where B is the vector of magnetic fields measured by the magnetic sensors, G is the lead field matrix, and J is the vector of source current in the brain. In practice, nLtm and J is usually a sparse vector. In this paper, we employ a complete reconstruction criterion to estimate the maximum number of active sources in the model or equivalently the volume of the active areas that guarantees a stable solution to the MEG inverse problem. Based on some prior information about the volume of the active areas, we then evaluate the stability of the solution with the employed model. Our approach guarantees an error upper bound on the solution with a certain number of active points. In the experiments, we have demonstrated the technique using some simulations.

关键词： Epilepsy Inverse problems Magnetic field measurement Magnetic sensors Spatial resolution Brain modeling Current measurement Magnetoencephalography Sparse matrices Cost function

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A probabilistic framework for content-based diagnosis of retinal disease

A probabilistic framework for content-based diagnosis of ret...

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29th Annual International Conference of IEEE-EMBS, engineering in Medicine and Biology Society, EMBC'07

作者： Tobin, Kenneth W. Abdelrahman, Mohamed Chaum, Edward Govindasamy, V. Priya Karnowski, Thomas P. IEEE Image Science and Machine Vision Group Oak Ridge National Laboratory Oak Ridge TN 37831-6075 United States Electrical and Computer Engineering Dept. Tennessee Tech. University Cookeville TN 38505-0001 United States Department of Retinal Diseases Hamilton Eye Institute University of Tennessee Memphis TN 38163 United States

ISBN: (纸本)1424407885

Diabetic retinopathy is the leading cause of blindness in the working age population in the industrialized world. computer assisted analysis has the potential to assist in the early detection of diabetes by regular screening of large populations. The widespread availability of digital fundus cameras today is leading to the accumulation of large image archives of diagnosed patient data that captures historical knowledge of retinal pathology. Through this research we are developing a content-based image retrieval method to verify our hypothesis that retinal pathology can be identified and quantified from visually similar retinal images in an image archive. We will present diagnostic results for specificity and sensitivity on a population of 395 fundus images representing the normal fundus and 14 stratified disease states. © 2007 IEEE.

关键词： Diseases

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