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MRI-based semi-automatic pelvimetry measurement for pelvic organ prolapse diagnosis

MRI-based semi-automatic pelvimetry measurement for pelvic o...

引用

International Symposium on signal processing and Its applications (ISSPA)

作者： Sinan Onal Susana Lai-Yuen Stuart Hart Paul Bao Alfredo Weitzenfeld University of South Florida Tampa FL US University of South Florida Tampa USA

ISBN: (纸本)9781467303811

Magnetic resonance imaging (MRI) pelvimetry measurements are useful in the diagnosis of pelvic organ prolapse given the inaccuracy of clinical examination. However, MRI measurements are currently performed manually and can be inconsistent, time-consuming and inaccurate. In this paper, we present a scheme for semi-automatic measurements on MR images based on multi scale wavelet analysis. The experiments on the MR images show that the presented scheme can detect the points of reference on the pelvic bone structure to determine the lines needed for the assessment of pelvic organ prolapse. This may lead towards more accurate and faster pelvic organ prolapse diagnosis on dynamic MR studies, and possible screening procedures for predicting predisposition to pelvic organ prolapse by radiologic evaluation of pelvimetry measurements.

关键词： image edge detection Magnetic resonance imaging Approximation methods Surgery Joints wavelet analysis image segmentation

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Development of Discrete wavelet Transform (DWT) toolbox for signal processing applications

Development of Discrete Wavelet Transform (DWT) toolbox for ...

引用

International conference on Biomedical Engineering (ICoBE)

作者： Mousa K. Wali M. Murugappan R. Badlishah Ahmad Bong Siao Zheng School of Computer Engineering Universiti Malaysia Perlis Kuala Perlis Perlis Malaysia School of Mechatronic Engineering Universiti Malaysia Perlis Arau Perlis Malaysia

Discrete wavelet Transform (DWT) plays a significant role in several image and signal processing applications. Most of the researchers are using different wavelet toolboxes for their application and research investigation. In this work, we presented a development of DWT toolbox using Visual Basic 6.5. This starting version of this software package is developed to offer more user friendliness and allow the user to choose different types of wavelet functions from three different wavelet families (Daubechies, Symlet, and Coiflet), and number of decomposition level. This software is also have an ability to plot the frequency spectrum of user specific decomposition level using Fast Fourier Transform (FFT) and to provide a option for saving the DWT output in either .txt or .xls format for any further investigation. This graphical user interface (GUI) is designed for handling any type of input signal either in offline or online and gives more accurate results over conventional tool boxes.

关键词： Discrete wavelet transforms Graphical user interfaces Filter banks Software Approximation methods

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Blurred image Deconvolution Using Gaussian Scale Mixtures Model in wavelet Domain

Blurred Image Deconvolution Using Gaussian Scale Mixtures Mo...

引用

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

作者： Muhammad Hanif Abd-Krim Seghouane National ICT Australia College of Engineering and Computer Science Canberra Australia

image restoration (deconvolution) is a basic step for image processing, analysis and computer vision. We addressed blurred image deconvolution problem using Expectation maximization (EM) based approach in the wavelet domain. The sparsity property of wavelet coefficients is modelled using the class of Gaussian Scale Mixture (GSM), which represents the heavy-tailed statistical distribution. The maximum a posterior (MAP) estimate is computed using EM, where scale factors of GSM plays the role of hidden variables. The estimated hidden scaling variables are then used to restore the original image. Although similar formulations have been proposed before but the resulting optimization problems have been computationally demanding and sometimes depends heavily on the initial values of parameters. We proposed an optimized Bayesian approach in wavelet domain to restore an image degraded by linear distortion (e.g., blur) and additive Gaussian noise. Simulation results are presented to demonstrate the quality of our method, over a wide range of blur and noise level, both visually and in terms of signal to noise ratio.

关键词： Deconvolution image restoration GSM wavelet domain Noise Bayesian methods Discrete Fourier transforms

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Privacy protected image denoising with secret shares

Privacy protected image denoising with secret shares

引用

IEEE International conference on image processing

作者： Sayed M. SaghaianNejadEsfahani Ying Luo Sen-ching S. Cheung Department of Electrical & Computer Engineering University of Kentucky Lexington USA

The proliferation of digital cameras, wireless networks and distributed computing make sharing of visual data easier than ever. Such casual exchange of data, however, has increasingly raised questions on how sensitive visual information can be protected. Encrypted-domain signal processing techniques based on homomorphic encryption and garbled circuits are increasingly applied for such applications. Their high computation and communication complexity, however, are not suitable for pixel-level processing. In this paper, we propose an alternative approach of using information-theoretically secure protocols over multiple non-colluding semi-honest computing agents. The proposed protocols are based on classical Shamir's secret sharing scheme which supports multiplication and addition in the random-share domain. We extend the sharing scheme to handle other fundamental signal processing operations and use them to develop a novel privacy-protected wavelet denoising scheme over three computing agents. Our experimental results demonstrate the viability of using information-theoretic secure protocols to safeguard privacy in distributed pixel-level processing.

关键词： Cryptography Protocols Noise reduction Complexity theory Discrete wavelet transforms Frequency modulation

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Multi-resolution filter banks for enhanced SAR imaging

Multi-resolution filter banks for enhanced SAR imaging

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International conference on Systems and Informatics (ICSAI)

作者： Ehsan O. Sheybani Giti Javidi Virginia State University Petersburg VA USA

SAR finds applications in many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract images from SAR radar data. Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem. This paper discusses innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms.

关键词： wavelet transforms Algorithm design and analysis image coding image resolution signal processing algorithms Noise reduction

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Theoretical distortion estimation in L-infinite wavelet-based coding of semi-regular meshes

Theoretical distortion estimation in L-infinite wavelet-base...

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European signal processing conference (EUSIPCO)

作者： Ruxandra Florea Leon Denis Jan Lievens Peter Schelkens Adrian Munteanu Interdisciplinary Institute for BroadBand Technology Ghent Belgium Department of Electronics and Informatics (ETRO) Vrije Universiteit Brussel Brussels Belgium

Subdivision-based wavelet coding techniques yield state-of-the-art performance in scalable compression of semi-regular meshes. However, all these codecs make use of the L-2 distortion metric, which gives only a good approximation of the global error produced by lossy coding of the wavelet coefficients. The L-infinite metric has been proven to be a suitable metric for applications where controlling the local, maximum error on each vertex is of critical importance. In this context, an upper bound formulation for the L-infinite distortion for a wavelet-based coding scheme operating on semi-regular meshes is derived. In addition, we propose a rate-distortion optimization algorithm that minimizes the rate for any target L-infinite distortion. It is shown that our L-infinite coding system outperforms the state-of-the-art and that an L-2 driven coding approach for semi-regular meshes loses ground to its L-infinite driven version when the goal is to have a tight control on the local reconstruction error.

关键词： Encoding Codecs image coding wavelet transforms Measurement Approximation methods

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Rapid prototyping of three-dimensional transform for medical image compression

Rapid prototyping of three-dimensional transform for medical...

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International Symposium on signal processing and Its applications (ISSPA)

作者： Noor Huda Ja'afar Afandi Ahmad Abbes Amira Department of Computer Engineering Universiti Tun Hussein Onn Malaysia (UTHM) Johor Malaysia Department of Electrical Engineering College of Engineering Qatar University Doha Qatar

ISBN: (纸本)9781467303811

This paper presents the design and implementation of three-dimensional (3-D) Haar and Daubechies with transpose based method for medical image compression. Due to the separability property of the multi-dimensional Haar and Daubechies, the proposed architecture has been implemented using a cascade of three N-point one-dimensional (1-D) Haar/Daubechies and two transpose memories for a 3-D volume of N×N×N suitable for real-time 3-D medical imaging applications. Two architectures were synthesised using VHDL and implemented on Altera ® Cyclone II (EP2C15AF484C6) field programmable gate array (FPGA). Experimental results and an analysis of the area, power consumption and maximum frequency are discussed in this paper.

关键词： Computer architecture Biomedical imaging wavelet transforms image coding Power demand Algorithm design and analysis

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Evaluation of sparsifying algorithms for speech signals

Evaluation of sparsifying algorithms for speech signals

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International conference on Computer and Communication Engineering, ICCCE

作者： Liban A. Kassim Othman O. Khalifa T. S. Gunawan Faculty of Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

Sparse representations of signals have been used in many areas of signal and image processing. It has also played an important role in compressive sensing algorithms since it performs well in sparse signals. A sparse representation is one in which small number of coefficients contain large proportion of the energy. Sparsity is important also in speech compression and coding, where the signal can be compressed in pre-processing stages. It leads to efficient and robust methods for compression, detection denoising and signal separation. The objective of this paper is to evaluate several transforms which is used to sparsify the speech signals. Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Discrete wavelet Transform (DWT) will be compared and evaluated based on Gini Index. Sparsity properties and measures will be reviewed in this paper. Finally, sparse applications in speech compression and compressive sensing will be discussed.

关键词： Discrete cosine transforms Discrete wavelet transforms Indexes image coding Speech

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PATCH-BASED FEATURE MAPS FOR PIXEL-LEVEL image SEGMENTATION

PATCH-BASED FEATURE MAPS FOR PIXEL-LEVEL IMAGE SEGMENTATION

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European signal processing conference

作者： Shuoying Cao Saadia Iftikhar Anil Anthony Bharath Imperial College London

ISBN: (纸本)9781467310680

In this paper, we describe the use of phase-invariant complex wavelet filters, coupled to a training process involving a small, high-quality training dataset, to build an image segmentation system capable of performing in very low signal-to-noise, and under conditions of strong object-background contrast change. The three main components of our approach are: i) a patch-based feature description of local phase-invariant orientation fields;ii) a priori ground-truth data;iii) a machine learning method, such as Multilayer Perceptron (MLP) or kernel-based Support Vector Machine (SVM), to build an accurate classifier that is customised to the segmentation problem. A key feature of the approach is that it may be easily retrained and is, therefore, more adaptable to different imaging modalities. A representation of phase-invariant local image orientation using geometric algebra is first introduced;this is important to the patch-based approach. The quality of our trained systems is then assessed using Receiver Operating Characteristic (ROC) curves in two different biomedical applications: the human retinal vessel-bed in colour fun-dus images from the publicly available DRIVE database, and the rabbit endothelial cell boundaries of thoracic aorta microscopy images.

关键词： Segmentation Visual features Geometric algebra Multilayer Perceptron Support Vector Machine Microscopy Retinal imaging images image orientation wavelet filter maps master element Support Vector Network

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ℓ1-adapted non separable vector lifting schemes for stereo image coding

ℓ1-adapted non separable vector lifting schemes for stereo ...

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European signal processing conference (EUSIPCO)

作者： M. Kaaniche B. Pesquet-Popescu J.-C. Pesquet Signal and Image Proc. Department Telecom Paris Tech Paris France LIGM and UMR-CNRS 8049 Champs-sur-Marne Université Paris-Est Marne-la-Vallee France

Due to the great interest of stereo images in several applications, it becomes mandatory to improve the efficiency of existing coding techniques. For this purpose, many research works have been developed. The basic idea behind most of the reported methods consists of applying an inter-view prediction via the estimated disparity map followed by a separable wavelet transform. In this paper, we propose to use a two-dimensional non separable decomposition based on the concept of vector lifting scheme. Furthermore, we focus on the optimization of all the lifting operators employed with the left and right images. Experimental results carried out on different stereo images show the benefits which can be drawn from the proposed coding method.

关键词： image coding Vectors Transforms Optimization Bit rate Joints signal processing

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