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International Conference on computer and Information Technology (ICCIT)

作者： R. Tajallipour Khan Wahid Multimedia Processing and Prototyping Laboratory Department of Electrical and Computer Engineering University of Saskatchewan Saskatoon SAS Canada

The paper presents an efficient adaptive Lempel-Ziv-Welch (LZW) data compression algorithm for medical image compression applications. The encoder is based on custom-sized library and custom-valued threshold where both the size of the library and the threshold parameters are adjusted by the user. The algorithm is compared with other existing compression schemes applicable to medical imaging. Because of the adaptive nature, the output of encoder can be controlled as per the bandwidth requirement of the data transmission and storage capacity. The simulation is carried out on several medical and endoscopic images and the results show that a compression ratio of 94% can be achieved with a reconstruction quality of 40 dB. The estimated energy consumption is 21.6mJ for a 256×256 color image with a frame rate of 2fps.

关键词： Biomedical imaging

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A system for automatic HPV typing via PCR-RFLP gel electrophoresis

A system for automatic HPV typing via PCR-RFLP gel electroph...

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2011 7th IEEE International Conference on Automation Science and engineering, CASE 2011

作者： Maramis, Christos F. Delopoulos, Anastasios N. Lambropoulos, Alexandros F. Katafigiotis, Sokratis P. Information Processing Laboratory - Multimedia Understanding Group Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki 54124 Greece 1st Department of Obstetrics and Gynecology General Regional Hospital Papageorgiou Aristotle University of Thessaloniki Thessaloniki 54124 Greece

ISBN: (纸本)9781457717307

The identification of the types of the human papillomavirus (HPV) that have infected a female patient provides valuable information as regards to her risk for developing cervical cancer. A widely used method for performing the above task (namely HPV typing) is PCR-RFLP gel electrophoresis. However, the conventional HPV typing protocol is error-prone and resource-ineffective due to lack of interaction between the phases involved in it. In order to treat these shortcomings, we introduce a novel HPV typing system that can be built upon widely available laboratory equipment. The proposed workflow of the system automates the task of HPV typing via PCRRFLP gel electrophoresis. The proof-of-concept of the proposed methodology is evaluated via an experiment that emulates the operation of the introduced system on a set of real HPV data. © 2011 IEEE.

关键词： Polymerase chain reaction

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Semantic web service composition using answer set planning

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International Journal of Advancements in Computing Technology 2011年第5期3卷 20-31页

作者： Qian, Jun-Yan Huang, Guo-Wang Zhao, Ling-Zhong National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Department of Computer science and engineering Guilin University of Electronic Technology Guilin 541004 China

This paper presents a method that adapting planning description to bring the semantic information into play for service composition through action language C. It shows how service descriptions can be expressed by preconditions and effects and the action language C provides a richer syntax and semantic for complex service descriptions. We also presents the algorithm of Translating semantic Web service described by OWL-S to action language C. Thanks to the structured description and the powerful expression of C, we only consider the initial Situation and the desired goal ignoring details of transition and planning. At last we use satisfiability planning to solve the planning problem by translating the action language into disjunctive logic program.

关键词： Web services

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A New NSCT Based Contrast Enhancement Algorithm for Amplification of Early Signs of Ischemic Stroke in Brain CT Images

A New NSCT Based Contrast Enhancement Algorithm for Amplific...

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Iranian Machine Vision and Image processing (MVIP)

作者： Mehdi Sajjadi Rassoul Amirfattahi Mohammad Reza Ahmadzadeh Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Brain CT images are extensively used in detection of Cerebrovascular Accidents (CVA). But CT scan is not really a sensitive test for diagnosis of ischemic stroke. Most of the times, early CT images barely show or even don 't show any noticeable sign of ischemia. But it is possible to put emphasis on subtle signs of ischemia by means of image contrast enhancement. Contrast enhancement using multiscale transforms is one of the most popular approaches in recent years. Nonsubsampled Contourlet Transform (NSCT) is a directional multiscale transform that is able to take geometrical structures into account. In this paper we are about to customize this transform and improve its performance in contrast enhancement of brain CT images. To this end, we propose a set of simpler and more efficient filters for Nonsubsampled Pyramid (NSP) and introduce an improved method for modification of directional subbands' coefficients.

关键词： Filter banks Finite impulse response filter Computed tomography Equations Wavelet transforms Image enhancement

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Semi-supervised learning in nonstationary environments

Semi-supervised learning in nonstationary environments

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International Joint Conference on Neural Networks (IJCNN)

作者： Gregory Ditzler Robi Polikar Signal Processing and Pattern Recognition Laboratory in the Electrical & Computer Engineering Department Rowan University Glassboro NJ USA

Learning in nonstationary environments, also called learning concept drift, has been receiving increasing attention due to increasingly large number of applications that generate data with drifting distributions. These applications are usually associated with streaming data, either online or in batches, and concept drift algorithms are trained to detect and track the drifting concepts. While concept drift itself is a significantly more complex problem than the traditional machine learning paradigm of data coming from a fixed distribution, the problem is further complicated when obtaining labeled data is expensive, and training must rely, in part, on unlabelled data. Independently from concept drift research, semi-supervised approaches have been developed for learning from (limited) labeled and (abundant) unlabeled data; however, such approaches have been largely absent in concept drift literature. In this contribution, we describe an ensemble of classifiers based approach that takes advantage of both labeled and unlabeled data in addressing concept drift: available labeled data are used to generate classifiers, whose voting weights are determined based on the distances between Gaussian mixture model components trained on both labeled and unlabeled data in a drifting environment.

关键词： Classification algorithms Data models Clustering algorithms Training data Training Testing Algorithm design and analysis

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A block-based 2D Discrete Wavelet Transform structure with new scan method for overlapped sections

A block-based 2D Discrete Wavelet Transform structure with n...

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Middle East Conference on Biomedical engineering (MECBME)

作者： Sayed Ahmad Salehi Rasoul Amirfattahi Department of Electrical and Computer Engineering Digital Signal Processing Research Laboratory Isfahan University of Technology Isfahan Iran

Regarding internal memory size, we proposed a new scan method for block-based structure to provide an efficient parametric structure for two Dimensional Discrete Wavelet Transform (2-D DWT). The main challenge in 2-D DWT structure is the amount of internal memory required to produce wavelet coefficients. The previous structures need fixed memory size depend on input frame size, but in proposed architecture, memory size is parametric and in trade off with the number of output memory access. Lifting scheme is incorporated to implement DWT.

关键词： Discrete wavelet transforms Memory management Hardware Pixel

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Elastic Shape Registration Using an Incremental Free Form Deformation Approach with the ICP Algorithm

Elastic Shape Registration Using an Incremental Free Form De...

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Canadian Conference on computer and Robot Vision, CRV

作者： Hossam Abdelmunim Aly A. Farag Computer & Systems Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt Computer Vision and Image Processing Laboratory Electrical & Computer Engineering Department University of Louisville KY USA

Shape registration is one of the most challenging problems in computer vision and medical imaging. The process is affected by the way the shape is represented and the form of transformation used to move the source shape. Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point-based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as a criteria to establish point correspondences in each level of the IFFD framework. The free form deformation (FFD) is well known in the literature and works by forming a lattice of control points that can move and hence deform the domain grid points smoothly and uniformly under some shape constrains. The control lattice resolution is increased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems.

关键词： Shape Lattices Iterative closest point algorithm Image resolution Mathematical model Equations Energy resolution

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Evaluation of some physiological statements about seizure, using processing of epileptic EEG signals

Evaluation of some physiological statements about seizure, u...

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Iranian Conference on electrical engineering (ICEE)

作者： F. Shayegh R. Amirfattahi S. Sadri K. Ansari-Asl Digital signal Processing Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Iran Electrical Department Engineering Faculty Shahid Chamran University of Ahvaz Iran

Seizure genesis is usually attributed to imbalance of the excitation and inhibition activities of neurons. It is claimed that slow inhibition mechanism is responsible for controlling the variations of the excitation mechanism, and any deficiency in this function will lead to disturbance of their natural balance. Fast inhibition mechanism is also known to collaborate with slow inhibitory processes. Any proof about the excitation and inhibition mechanisms refers to the ex-vivo or in-vitro experiments, i.e. from the microscopic point of view. Up to now, there is not a straight road into evaluating these hypotheses from the macroscopic view. In this paper we try to interpret the excitation-inhibition sequences extracted from some depth-EEG signals through an identification-based procedure. The aim is to check out whether the statements gained from microscopic observations are re-established in population of neurons in the case of MTLE or not. Using Neyman-Pearson hypothesis test technique we try to answer these questions. We observe that even in population of neurons slow inhibition is responsible for compensating excitatory processes to balance inhibitory /excitatory ratio, such that when it is impaired causes seizures to arise; also the average fast inhibitory process of population of neurons follows its slow inhibition dynamics. Also, we check the differentiation of the excitation-inhibition ratio between normal and ictal states, as well as between normal and pre-ictal states. Ictal activity is properly a state of abnormal high excitation-inhibition ratio but before beginning of seizures there are not unique patterns.

关键词： Brain modeling Electroencephalography Noise Mathematical model Neurons Cost function Equations

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Elastic shape registration using an incremental free form deformation approach with the ICP algorithm

Elastic shape registration using an incremental free form de...

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IEEE International Conference on Image processing

作者： Hossam Abdelmunim Aly A. Farag Computer & Systems Engineering Department Ain Shams University Cairo Egypt Computer Vision and Image Processing Laboratory Electrical & Computer Engineering Department University of Louisville Louisville KY USA

Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point- based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as criteria to establish point correspondences in each level of the IFFD framework. The IFFD control lattice resolution is in- creased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems.

关键词： Shape Lattices Iterative closest point algorithm Equations Spline Mathematical model Three dimensional displays

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A compressive sensing based compressed neural network for sound source localization

A compressive sensing based compressed neural network for so...

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International Symposium on Artificial Intelligence and Signal processing (AISP)

作者： Mehdi Banitalebi Dehkordi Hamid Reza Abutalebi Hossein Ghanei Speech Processing Research Laboratory Electrical and Computer Engineering Department Yazd University Yazd Iran Electrical and Computer Engineering Department Yazd University Yazd Iran Idiap Research Institute Martigny Switzerland

Microphone arrays are today employed to specify the sound source locations in numerous real time applications such as speech processing in large rooms or acoustic echo cancellation. Signal sources may exist in the near field or far field with respect to the microphones. Current Neural Networks (NNs) based source localization approaches assume far field narrowband sources. One of the important limitations of these NN-based approaches is making balance between computational complexity and the development of NNs; an architecture that is too large or too small will affect the performance in terms of generalization and computational cost. In the previous analysis, saliency subject has been employed to determine the most suitable structure, however, it is time-consuming and the performance is not robust. In this paper, a family of new algorithms for compression of NNs is presented based on Compressive Sampling (CS) theory. The proposed framework makes it possible to find a sparse structure for NNs, and then the designed neural network is compressed by using CS. The key difference between our algorithm and the state-of-the-art techniques is that the mapping is continuously done using the most effective features; therefore, the proposed method has a fast convergence. The empirical work demonstrates that the proposed algorithm is an effective alternative to traditional methods in terms of accuracy and computational complexity.

关键词： Artificial neural networks Microphones Sparse matrices Approximation algorithms Training Biological neural networks Classification algorithms

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