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

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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Channel-aware rate-distortion optimized leaky motion prediction

Channel-aware rate-distortion optimized leaky motion predict...

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IEEE International Conference on image processing

作者： Zhen Li E.J. Delp Video and Image Processing Laboratory(VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

Leaky motion prediction techniques have been developed as a way to trade-off between video coding efficiency and drift error resilience. In this paper, we present a statistical analysis of leaky motion prediction in the presence of channel errors. We assume the encoder has some basic knowledge of the channel such as the channel error pattern and error rate. We derive a closed-form expression of the rate distortion function and find the analytic solution for the leaky motion prediction parameter. Two examples are presented 10 demonstrate the results.

关键词： Rate-distortion Video coding Motion analysis Decoding Bandwidth image coding image reconstruction Resilience image processing Laboratories

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Markov random field estimation of lost DCT coefficients in JPEG due to packet errors

Markov random field estimation of lost DCT coefficients in J...

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IEEE International Conference on image processing

作者： J. Yang E.J. Delp Vidco and Image Processing Laboratory VIPER School or Electrical and Computer Engineering Purdue University West Lafayette IN USA

Interleaving is used before the encoding of source symbols in JPEG to reduce visual artifacts due to lost packets because interleaving distributes the locations of errors. The recovery of lost DCT coefficients in interleaved image compression is investigated in this paper. To restore the lost coefficients, an Maximum a Posteriori (MAP) estimate for the DCT coefficients is proposed. Under the assumption of a Gauss-Markov Random Field (GMRF) model in the pixel domain, the MAP estimate for the lost DCT coefficients is derived.

关键词： Markov random fields Discrete cosine transforms Decoding Interleaved codes image coding Automatic repeat request Streaming media image restoration Laboratories Communication networks

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Adaptive lossless video compression using an integer wavelet transform

Adaptive lossless video compression using an integer wavelet...

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IEEE International Conference on image processing

作者： S.-G. Park E.J. Delp H. Yu Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Corporate Research Group Thomson Inc. Indianapolis IN USA

In this paper, we describe an adaptive lossless compression algorithm for color video sequences utilizing backward adaptive temporal prediction and an integer wavelet transform. We exploit two redundancies in color video sequences, specifically spatial and temporal redundancies. We show that an adaptive scheme exploiting the two redundancies has better compression performance than lossless compression of individual image frames. The result of the proposed scheme is compared to current video compression algorithms.

关键词： Video compression Wavelet transforms image coding Redundancy Video sequences image edge detection Decorrelation Frequency image processing Laboratories

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Full-field mammogram analysis based on the identification of normal regions

Full-field mammogram analysis based on the identification of...

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IEEE International Symposium on Biomedical Imaging

作者： Y. Sun C. Babbs E.J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Basic Medical Sciences School of Veterinary Medicine Purdue University West Lafayette IN USA

We present a new method for full-field mammogram analysis. A mammogram is analyzed region by region and is classified as normal or abnormal. We present methods for extracting features that can be used to distinguish normal and abnormal regions of a mammogram. We describe our classifier technique that uses a unique reclassification method to boost the classification performance. We have tested this technique on a set of ground-truth full-field mammograms.

关键词： Feature extraction Breast cancer Cancer detection Mammography Biomedical imaging image analysis Delta-sigma modulation Spatial databases image databases Optical scattering

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Activation detection in multi-subject studies of fMRI using GLRT

Activation detection in multi-subject studies of fMRI using ...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S.M. Shams G.A. Hossein-Zadeh H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics University of Tehran School of Cognitive Sciences Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Institute for Studies in Theoretical Physics and Mathematics and Medical Image Analysis Laboratory Henry Ford Health System University of Tehran School of Cognitive Sciences Iran

A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the flexibility of method in detecting different shapes of hemodynamic response. The proposed multivariate method can be applied to group studies where the conventional cross-correlation method cannot be used due to its univariate property. This method is applied to both experimental and simulated fMRI data and the results are compared to those of general linear model (GLM). We show that the proposed method detects more significant activated regions in analyzing experimental data and more true voxels in simulated data

关键词： Testing Hemodynamics Brain modeling Process control Intelligent control Physics computing Mathematics Time series analysis Magnetic resonance imaging Data analysis

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Normal mammogram classification based on a support vector machine utilizing crossed distribution features

Normal mammogram classification based on a support vector ma...

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

作者： W. Chiracharit Y. Sun P. Kumhom K. Chamnongthai C. Babbs E.J. Delp Electronics and Telecom. Engineering Department King Mongkut's University of Technology Thonburi Bangkok Thailand Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University IN USA Department of Basic Medical Sciences School of Veterinary Medicine Purdue University IN USA

Automatic classification of normal mammograms, which constitute a majority of screening mammograms, is a new approach to computer-aided diagnosis of breast cancer. This approach may be limited, however, by non-separable "crossed" distributions of features that are extracted from digitized mammograms. This work presents a method of mapping such non-separable input features into a new set of separable features that can be utilized, together with ordinary "uncrossed" features, by a support vector machine (SVM) classifier. The results of the proposed scheme show improved performance with 80% sensitivity and 95% specificity.

关键词： Support vector machines Support vector machine classification Training data Data mining Biomedical engineering Biomedical imaging computer aided diagnosis Breast cancer Aging Mammography

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Multimodality image registration and fusion using neural network

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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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Statistically Robust Approach to Lens Distortion Calibration with Model Selection

Statistically Robust Approach to Lens Distortion Calibration...

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

作者： Moumen Taha El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Dept. Assiut University Assiut Egypt Computer Vision and Image Processing Lab. University of Louisville Louisville KY

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement in one form or another,we present an approach to distortion calibration based on the robust the-least-median-of-squares (LMedS) estimator. Our approach is thus able to proceed in a ful ly-automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3D linear segments. Our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. Moreover we propose a method for distortion model selection based on geometrical *** experiments to evaluate the performance of this approach on synthetic and real data are reported.

关键词： Nonlinear distortion Calibration Robustness Lenses Cameras image edge detection Distortion measurement

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Video reconstructions in dentistry

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Orthodontics and Craniofacial Research 2003年第SUPPL1期6卷 108-116页

作者： Farag, A.A. Eid, A. Electrical and computer Engineering Department University of Louisville Computer Vision and Image Processing Laboratory Louisville KY 40292 United States

Objectives: To present two practical techniques for threedimensional (3D) modeling of the human jaw from a sequence of intra-oral images. Design: A data acquisition system consists of: 3D digitizing arm, CCD camera and a laser projector in addition to a software module of two 3D modeling techniques;shape from shading (SFS) and space carving (SC). Setting and sample population - Several experiments have been conducted on a sample of students at the computer vision and image processing (CVIP) laboratory at the University of Louisville, Louisville, KY. Other experiments were performed on solid models of human jaw. Experimental variable: The SFS technique, using perspective projection and camera calibration, extracts the 3D information from a sequence of two-dimensional images of the jaw. Data fusion of range data and 3D registration techniques develop the complete jaw model. The SC approach is implemented on a sequence of calibrated images. On the two reconstructions, we fit a mesh model to the data, in order to create a solid 3D model. Outcome measure: The accuracy of the reconstructed 3D model of human jaw is calculated based on the measurements on real jaws. Results: The SFS-based technique seems to provide more faithful information about the shape of the tooth tops. However, the SC algorithm successfully reconstructed 3D models of the human jaw with sub-millimeter accuracy, which is as accurate as (or even better than) the first technique without using any range measurements or laser projectors. The average error in distance calculation was found to be 0.74 mm, which is an acceptable resolution for many orthodontics and maxillofacial applications. Conclusion: Accurate 3D reconstruction of the human jaw enables many orthodontics and dental imaging researchfindings to be applied directly to a digital jaw model - not to a cast - using computer vision and medical imaging tools. © 2003 Blackwell Munksgaard.

关键词： Data fusion Jaw modeling Registration Shape from shading Space carving

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