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Prostate Cancer Biomarker Selection through a Novel Combination of Sequential Global Thresholding, Particle Swarm Optimization, and PNN Classification of MS-Spectra

Prostate Cancer Biomarker Selection through a Novel Combinat...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Panagiotis Bougioukos Dionisis Cavouras Antonis Daskalakis Spiros Kostopoulos George Nikiforidis Anastasios Bezerianos Department of Medical Physics School of Medicine University of Patras Rion Greece Medical Signal and Image Processing Laboratory Department of Medical Instrumentation Technology Technological Educational Institute of Athens Athens Greece

Proteomic analysis using mass spectrometry data is a powerful tool for biomarker discovery. However, proteomic data suffers from two crucial problems i/ are inherently very noisy and ii/ the number of features that finally characterize each spectrum is usually very large. In the present study, a well-established framework of data preprocessing steps was developed to deal with the problem of noise, incorporating smoothing, normalization, peak detection, and peak alignment algorithms. In addition, to alleviate the problem of feature dimensionality, a novel iterative peak selection method was developed for choosing peaks (features) from the pre- processed spectra, based on sequential global thresholding followed by particle swarm optimization. These features were fed into a probabilistic neural network algorithm, in order to discriminate healthy from prostate cancer cases and, thus, to determine, through the algorithm's optimal design, biomarkers related to prostate cancer.

关键词： Prostate cancer Biomarkers Particle swarm optimization Iterative algorithms Proteomics Mass spectroscopy Data preprocessing Smoothing methods Iterative methods Neural networks

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Colour-Texture based image analysis method for assessing the Hormone Receptors status in Breast tissue sections

Colour-Texture based image analysis method for assessing the...

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

作者： Spiros Kostopoulos Dionisis Cavouras Antonis Daskalakis Panagiotis Bougioukos Pantelis Georgiadis George C. Kagadis Ioannis Kalatzis Panagiota Ravazoula George Nikiforidis Medical Image Processing and Analysis Group (MIPA) Laboratory of Medical Physics School of Medicine University of Patras Rio-Patras Greece Medical Image and Signal Processing Laboratory Department of Medical Instrumentation Technology Technological Education Institute of Athens Athens Greece Department of Pathology University Hospital of Patras Rio-Patras Greece

Hormone receptors have been used in prognosis of breast carcinomas and their positive status is of clinical value in hormonal therapy. Determination of this status is based on the subjective visual inspection of the stained nuclei in the specimens. The aim of this study was the assessment of the estrogen receptor's (ER) positive status of breast carcinomas, by means of colour-texture based image analysis methodology. Twenty two cases of immunohistochemically (IHC) stained breast biopsies were initially assessed by a histopathologist for ER positive status, following a clinical scoring protocol. Custom-designed image analysis software was developed for automatically assessing the ER positive status, employing colour textural features and the k-Nearest Neighbor weighted votes classification algorithm. Computer-based image analysis system resulted in 86.4% overall accuracy and in 0.875 Kendall's coefficient of concordance (p<0.001), ranking correctly 19/22 cases. Colour-texture analysis of IHC stained specimens might have an impact in the quantitative assessment of ER status.

关键词： image color analysis Biochemistry Breast tissue Erbium Medical treatment Inspection Immune system Breast biopsy Protocols Voting

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Face Recognition Research Based on Anti-Symmetrical Wavelet and Eigenface

Face Recognition Research Based on Anti-Symmetrical Wavelet ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qian Yin Zhi-Yong Yuan Ying Kong Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Wuhan University of China Wuhan China School of Computer Science & Technology Beijing Institute of Technology Beijing China

In this paper, a new human face recognition method based on anti-symmetrical biorthogonal wavelet transformation (ASBWT) and eigenface was proposed. First the anti-symmetrical biorthogonal wavelet is chosen to degrade the face image dimension, meanwhile complete the process of face location and segmentation; And then human face is reverted through the face space of eigenface, the traditional average human face is replaced in the within-class scatter matrix. This within-class scatter matrix is used to calculate within-class and between-class distance proportion as a rule function, calculate the twice eigenface through discrete Karhunen-Loeve transform (DKLT), and use singular value decomposition (SVD) method to calculate the eigenvector. Finally we compute the weights and classify the face images. The results show that the proposed method has higher recognition rate and more robust than the traditional eigenface analysis method.

关键词： Face recognition Scattering Matrix decomposition image coding Humans Matrices Degradation Robustness Wavelet analysis Fourier transforms

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Acoustic Model Enhancement: An Adaptation Technique for Speaker Verification Under Noisy Environments

Acoustic Model Enhancement: An Adaptation Technique for Spea...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： A. Moreno-Daniel J. A. Nolazco-Flores T. Wada B.-H. Juang Computer Science Department Tecnológico de Monterrey Monterrey Nuevo Leon Mexico Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA Tecnológico de Monterrey Mexico

This work presents an acoustic model adaptation method for speaker verification (SV) in environments with additive noise. In contrast to traditional acoustic model adaptation techniques that adapt the models parameters based on a model of the noise, acoustic model enhancement (AME) belongs to a new scheme in which the models are adapted to the speech enhancement strategy. The theoretical framework is presented for spectral subtraction (SS) as the enhancement technique and GMM as the acoustic models. In order to study the effect of additive noise only, a modified TIMIT dataset was used. The experimental setup uses two types of noise: one with fixed spectrum that helps as a proof of concept, and another with time-varying spectrum as a more realistic performance reference for AME. The results for this latter type show that at 20 dB SNR, the equal error rate (EER) dropped from 17% to around 8.9% when the noisy speech was enhanced with SS, whereas it further dropped to 8.1% with AME.

关键词： Adaptation model Loudspeakers Acoustic noise Working environment noise Speech enhancement Additive noise signal processing Robustness Access control Biometrics

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A Matrix Pseudo-Inversion Lemma and Its Application to Block-Based Adaptive Blind Deconvolution for MIMO Systems

A Matrix Pseudo-Inversion Lemma and Its Application to Block...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Kiyotaka Kohno Yujiro Inouye Mitsuru Kawamoto Shimane University Matsue Shimane Japan Laboratory for Advanced Brain Signal Processing RIKEN Wako Saitama Japan Information Technology Research Institute National Institute of Advanced Industrial Science and Technology Tsukuba Ibaraki Japan

The matrix inversion lemma gives an explicit formula of the inverse of a positive-definite matrix A added to a block of dyads (represented as BBH) as follows: (A + BB H ) -1 = A -1 - A -1 B(I + B H A -1 B) -1 B H A -1 . It is well-known in the literature that this formula is very useful to develop a block-based recursive least-squares algorithm for the block-based recursive identification of linear systems or the design of adaptive filters. We extend this result to the case when the matrix A is singular, and present a matrix pseudo-inversion lemma. Based on this result, we propose a block-based adaptive multi-channel super-exponential algorithm (BAMSEA). We present simulation results for the performance of the block-based algorithm in order to show the usefulness of the matrix pseudo-inversion lemma.

关键词： Deconvolution MIMO signal processing algorithms Adaptive signal processing Algorithm design and analysis Adaptive filters Programmable control Adaptive control Industrial electronics Centralized control

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Editorial: Knowledge engineering, semantics, and signal processing in audio - visual information retrieval

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IEEE Transactions on Circuits and Systems for Video technology 2007年第3期17卷 257-258页

作者： Izquierdo, Ebroul Zhang, Jian Sikora, Thomas Huang, Thomas S. Department of Electrical Engineering Queen Mary University of London London El 4NS United Kingdom Sydney Australia School of Computer Science and Engineering University of New South Wales Australia Communication Systems Group Technical University Berlin Berlin Germany ITG University of Illinois at Urbana-Champaign United States Department of Electrical and Computer Engineering Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Institute for Advanced Science and Technology United States Institute's Major Research Theme Human Computer Intelligent Interaction National Academy of Engineering Chinese Academies of Engineering and Sciences China International Association of Pattern Recognition Optical Society of American United States

No abstract available

关键词： Special issues and sections Knowledge engineering Information retrieval Audio-visual systems

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PDA-based system with teleradiology and image analysis capabilities

PDA-based system with teleradiology and image analysis capab...

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29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), vol.8

作者： Pantelis Georgiadis Dionisis Cavouras Antonis Daskalakis Koralia Sifaki Menelaos Malamas George Nikiforidis Ekaterini Solomon Medical Image Processing and Analysis Group (M.I.P.A.) Laboratory of Medical Physics School of Medicine University of Patras Greece Medical Signal and Image Processing Lab Department of Medical Instruments Technology Technological Education Institute of Athens Athens Greece MRI Unit General Hellenic Airforce Hospital Athens Greece Department of Radiology School of Medicine University of Patras Rio-Patras Greece

The aim of the present study was to design and implement a Personal Digital Assistant (PDA)-based teleradiology system incorporating image processing and analysis facilities for use in emergency situations within a hospital environment The system comprised a DICOM-server, connected to an MRI unit, 3 wireless access points, and 3 PDAs (HP iPaq rx3715). PDA application software was developed in MS Embedded Visual C++ 4.0. Each PDA can receive, load, process and analyze hi-quality static MR images. image processing includes gray-scale manipulation and spatial filtering techniques while image analysis incorporates a probabilistic neural network (PNN) classifier, which was optimally designed employing a suitable combination of textural features and was evaluated using the leave-one-out method. The PNN is capable of discriminating between three major types of human brain tumors with accuracy of 86.66%. The developed application may be useful as a mobile medical tele-consultation tool.

关键词： image analysis Personal digital assistants image processing Hospitals Magnetic resonance imaging Application software Gray-scale Filtering Biological neural networks Humans

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FDTD model of photonic crystal laser with four-energy-level gain media

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Jisuan Wuli/Chinese Journal of Computational Physics 2007年第4期24卷 452-456页

作者： Wang, Hong Ouyang, Zhengbiao Han, Yanling Meng, Qingsheng Center of THz Technology Shenzhen University Shenzhen 518060 China College of Engineering and Technology Shenzhen University Shenzhen 518060 China School of Physical Electronics University of Electronic Science and Technology of China Chengdu 610054 China Mathematics and Physics Department China University of Geosciences Wuhan 430074 China State Education Commission Laboratory for Image Processing and Intelligent Control Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

A model of one-dimensional photonic crystal laser with four-energy-level gain media is presented. The model consists of Maxwell-Bloch equations coupled with rate equations of electronic population in a photonic crystal laser system. The discretization of coupled equations is accomplished with finite different time domain (FDTD). Spectra, lasing mode, lasing threshold and dynamics of the photonic crystal laser are obtained. The simulation shows good agreement with theoretical predictions.

关键词： Photonic crystals

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Novel features for brain-computer interfaces

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Computational Intelligence and Neuroscience 2007年第unknown期2007卷 1-7页

作者： Woon, W.L. Cichocki, A. Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Wako Saitama 351-0198 2-1 Hirosawa Japan Malaysia University of Science and Technology Unit GL33 Petaling Jaya Selangor 47301 Kelana Square 17 Jalan SS7/26 Malaysia

While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which i... 详细信息

关键词： .Brain-Computer power spectrum BCI feature

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Challenging Issues in Multichannel Radar Array processing

Challenging Issues in Multichannel Radar Array Processing

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IEEE National Conference on Radar

作者： A. de Maio G. A. Fabrizio A. Farina W. L. Melvin L. Timmoneri Dipartimento di Ingegneria Elettronica e Delle Telecommunicationi Università Degli Studi di Napoli Federico II Napoli Italy Radar Signal Processing Group Intelligence Surveillance Reconnaissance Division Defence Science and Technology Organisation Edinburgh SA Australia SELEX Sistemi Integrati Rome Italy Sensors and Electromagnetic Applications Laboratory (SEAL) Georgia Institute of Technology Smyrna GA USA

This paper is focused on multichannel radar array processing and addresses some challenging issues concerning: the adaptation in nonstationary and nonhomogeneous environments, the value of Space-Time Adaptive processing (STAP) in an operational High Frequency (HF) radar system, the benefits resulting from the joint use of multiple (not colocated) transmitters and receivers, and the parallel implementation of the multichannel processor. The work follows on where the importance of a multichannel processing is demonstrated with reference to airborne, ground-based, and Over The Horizon (OTH) radar systems.

关键词： Array signal processing Spaceborne radar MIMO Radar signal processing Clutter Airborne radar Radar scattering Radar detection Radar applications Phased arrays

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