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An automatic computer-aided detection system for meniscal tears on magnetic resonance images

IEEE Transactions on Medical Imaging 2009年第8期28卷 1308-1316页

作者： Ramakrishna, Bharath Liu, Weimin Saiprasad, Ganesh Safdar, Nabile Chang, Chein-I Siddiqui, Khan Kim, W. Siegel, Eliot Chai, Jyh-Wen Chen, Clayton Chi-Chang Lee, San-Kan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD 21250 United States University of Maryland School of Medicine Baltimore MD 21201 United States Department of Electrical Engineering and Environmental Restoration Disaster Reduction Research Center National Chung Hsing University Taichung 402 Taiwan VA Maryland Health Care System Baltimore MD 21201 United States Hospital of the University of Pennsylvania Philadelphia PA 19104 United States Department of Radiology College of Medicine China Medical University Taichung 404 Taiwan Department of Radiology Taichung Veterans General Hospital Taichung 40705 Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung 406 Taiwan Department of Radiology Taichung Veterans General Hospital Taichung 407 Taiwan

Knee-related injuries including meniscal tears are common in both young athletes and the aging population, and require accurate diagnosis and surgical intervention when appropriate. With proper techniques and radiologists' experienced skills, confidence in detection of meniscal tears can be quite high. This paper develops a novel computer-aided detection (CAD) diagnostic system for automatic detection of meniscal tears in the knee. Evaluation of this CAD system using an archived database of images from 40 individuals with suspected knee injuries indicates that the sensitivity and specificity of the proposed CAD system are 83.87% and 75.19%, respectively, compared to the mean sensitivity and specificity of 77.41% and 81.39%, respectively, obtained by experienced radiologists in routine diagnosis without using the CAD. The experimental results suggest that the developed CAD system has great potential and promise in automatic detection of both simple and complex meniscal tears of the knee. © 2009 IEEE.

关键词： Magnetic resonance imaging

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Landmark Extraction from Echocardiography Sequence Based on Corner Detection Algorithms Using Product Moment Coefficient Matcher

Landmark Extraction from Echocardiography Sequence Based on ...

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International Conference on signal processing Systems, ICSPS

作者： Meysam Siyah Mansoory Hamid Behnam Emad Fatemi Zadeh Bio Medical Engineering Department Science and Research Branch Islamic Azad University슠 Tehran Iran Bio Medical Engineering Group Electrical Engineering Department Iran University of Science and Technology Tehran Iran Bio Medical Signal and Image Processing Laboratory School of Electrical Engineering Sharif University of Technology Tehran Iran

ISBN: (纸本)9781424442133

Landmark extraction is used as the first step of many vision tasks such as tracking, image registration, localization, image matching and recognition. Furthermore, landmarks are used to reduce the data flow and consequently the computational costs. In this paper we extracted landmarks from echocardiography sequence, our algorithm is based on corner extraction, and then we evaluate our algorithm with applying some test. For this purpose, we evaluated the detectors according to their repeatability, stability and landmark localization under changes in noise.

关键词： Echocardiography Detection algorithms Data mining Image registration Image matching Image recognition Computational efficiency Testing Detectors Stability

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Brain tissue classification using independent vector analysis (IVA) for magnetic resonance image

Brain tissue classification using independent vector analysi...

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2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009

作者： Chiou, Yaw-Jiunn Chen, Hsiang-Min Chai, Jyh Wen Chen, Clayton Chi-Chang Ouyang, Yen-Chieh Su, Wu-Chung Yang, Ching-Wen Lee, San-Kan Chang, Chein-I. Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology College of Medicine China Medical University Taichung Taiwan School of Medicine National Yang-Ming University Taipei Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung 406 Taiwan Computer Center Taichung Veterans General Hospital Taichung 407 Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780769536569

The purpose of this study is to present a new method, independent vector analysis (IVA), by extending independent component analysis (ICA) of univariate source signals to multivariate source signals on Magnetic Resonance Imaging (MRI). IVA is utilized to relief the limitation of the conventional ICA approach. The proposed method can resolve the permutation problem during individual ICA runs for group brain MR images. The proposed IVA method in conjunction with support vector machine (SVM), we can effectively separate the different part of gray, white matter and cerebrospinal fluid (CSF) from brain soft tissues. In order to demonstrate the proposed IVA-SVM method, experiments are conducted for performance analysis and evaluation. Simulation results show that using IVA can greatly release from the problem cause from traditional ICA to the situation of analyzing inconsistent results of MR image. © 2009 IEEE.

关键词： Magnetic resonance imaging

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Eye movement data modeling using a genetic algorithm

Eye movement data modeling using a genetic algorithm

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Congress on Evolutionary Computation

作者： Yun Zhang Hong Fu Zhen Liang Xiaoyu Zhao Zheru Chi Dagan Feng Xinbo Zhao School of Computer Science Northwestern University Evanston IL USA Center of Multimedia Signal Processing Hong Kong Polytechnic University Hong Kong China School of Information Technologies University of Sydney NSW Australia Key Laboratory of Contemporary Design & Integrated Manufacturing Technology Northwestern Polytechnical University Xi'an Shanxi China

We present a computational model of human eye movements based on a genetic algorithm (GA). The model can generate elemental raw eye movement data in a four-second eye viewing window with a 25 Hz sampling rate. Based on the physiology and psychology characters of human vision system, the fitness function of the GA model is constructed by taking into consideration of five factors including the saliency map, short time memory, saccades distribution, Region of Interest (ROI) map, and a retina model. Our model can produce the scan path of a subject viewing an image, not just several fixations points or artificial ROI's as in the other models. We have also developed both subjective and objective methods to evaluate the model by comparing its behavior with the real eye movement data collected from an eye tracker. Tested on 18 (9 times 2) images from both an obvious-object image group and a non-obvious-object image group, the subjective evaluations shows very close scores between the scan paths generated by the GA model and those real scan paths; for the objective evaluation, experimental results show that the distance between GA's scan paths and human scan paths of the same image has no significant difference by a probability of 78.9% on average.

关键词： Genetic algorithms Humans Computational modeling Sampling methods Physiology Psychology Machine vision Retina Tracking Testing

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Component analysis-based unsupervised linear spectral mixture analysis for hyperspectral imagery

Component analysis-based unsupervised linear spectral mixtur...

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Workshop on Hyperspectral Image and signal processing: Evolution in Remote Sensing, WHISPERS

作者： Xiaoli Jiao Yingzi Du Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science & Electrical Engineering University of Maryland Baltimore MD USA Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA Department of Electrical Engineering National Chung Hsing University Taichung Taiwan

One of the most challenging issues in unsupervised linear spectral mixture analysis (LSMA) is how to obtain unknown knowledge of target signatures referred to as virtual endmembers (VEs) directly from the data to be processed. This issue has never arisen in supervised LSMA where the VEs are either assumed to be known a priori or can be provided by visual inspection. With the recent advent of hyperspectral sensor technology many unknown and subtle signal sources can be uncovered and revealed without prior knowledge. This paper addresses this issue and develops a component analysis-based unsupervised LSMA where the desired VEs can be extracted by component analysis-based transforms directly from the data to be processed without appealing for prior knowledge. In order to substantiate the utility of the proposed approach extensive experiments are conducted for demonstration.

关键词： Image analysis Spectral analysis Hyperspectral imaging Independent component analysis Personal communication networks Inspection Statistics signal analysis Hyperspectral sensors Principal component analysis

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Highly robust ground moving target detection and relocation method for distributed satellites

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Frontiers of Electrical and Electronic Engineering in China 2008年第4期3卷 425-434页

作者： Ying LIU Guisheng LIAO Zhengguang ZHOU National Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China Nanjing Research Institute of Electronics Technology Nanjing 210013China

The performance of ground moving target detection for distributed satellites will be affected signifi-cantly when there is an image registration error,clutter decorrelation and array *** this paper,a new approach to moving target detection and relocation is proposed based on multi-channel and multi-pixel adap-tive signal processing in an image ***,multi-channel and multi-pixel joint data are equated to a simple array *** that there is an image registration error,the real steering vector of the moving target can be estimated through a space projection *** optimal beam forming approach is used to cancel clutter,and at the same time the cross-track velocity of the mov-ing target can be determined by searching for the peak value of the cost *** moving target can then be relocated on the SAR *** simulation results indicate that this method has a good robustness to image registration error,clutter decorrelation and array *** detection performance and the estimation accuracy are significantly improved.

关键词： distributed satellite ground moving target detection cost function image registration error optimal beam forming

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Brain Tissue Classification Using Independent Vector Analysis (IVA) for Magnetic Resonance Image

Brain Tissue Classification Using Independent Vector Analysi...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yaw-Jiunn Chiou Hsiang-Min Chen Jyh Wen Chai Clayton Chi-Chang Chen Yen-Chieh Ouyang Wu-Chung Su Ching-Wen Yang San-Kan Lee Chein-I Chang Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology College of Medicine China Medical University and Hospital Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and technology Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA

关键词： Brain Image analysis Magnetic analysis Magnetic resonance Independent component analysis Magnetic resonance imaging Support vector machines signal analysis Image resolution signal resolution

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Effects of terrestrial UV radiation on selected outdoor materials: An interdisciplinary approach

Effects of terrestrial UV radiation on selected outdoor mate...

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SPIE Optical Engineering + Applications

作者： Heikkilä, A. Kazadzis, S. Tolonen-Kivimäki, O. Meinander, O. Lindfors, A. Lakkala, K. Koskela, T. Kaurola, J. Sormanen, A. Kärhä, P. Naula-Iltanen, A. Syrjälä, S. Kaunismaa, M. Juhola, J. Ture, T. Feister, U. Kouremeti, N. Baisb, A. Vilaplana, J.M. Rodriguez, J.J. Guirado, C. Cuevas, E. Koskinen, J. Finnish Meteorological Institute R and D Erik Palménin aukio 1 00560 Helsinki Finland Aristotle University of Thessaloniki Laboratory of Atmospheric Physics 54124 Thessaloniki Greece Helsinki University of Technology Department of Signal Processing and Acoustics Otakaari 5 A 02150 Espoo Finland Tampere University of Technology Department of Materials Science Korkeakoulunkatu 6 33720 Tampere Finland Elastopoli Oy Nokiankatu 1 38210 Sastamala Finland Deutscher Wetterdienst Richard-Assmann-Observatorium Lindenberg Am Observatorium 12 15848 Lindenberg Germany Nacional de Técnica Aeroespacial Estación de Sondeos Atmosféricos El Arenosillo Ctra. San Juan del Puerto - Matalascañas Km.33 21130 Mazagon Huelva Spain Nacional de Meteorologia Spain Observatorio Atmosférico de Izaña C/ La Marina 20 Planta 6 38071 Santa Cruz de Tenerife Spain

ISBN: (纸本)9780819477521

Modern polymeric materials possess an ever increasing potential in a large variety of outdoor objects and structures offering an alternative for many traditional materials. In outdoor applications, however, polymers are subject to a phenomenon called weathering. This is primarily observed as unwanted property changes: yellowing or fading, chalking, blistering, and even severe erosion of the material surface. One of the major weathering factors is UV radiation. In spring 2005, the Finnish Meteorological Institute with its research and industrial partners launched a five-year material research project named UVEMA (UV radiation Effects on MAterials). Within the framework of the project, a weathering network of seven European sites was established. The network extends from the Canary Islands of Spain (latitude 28.5°N) to the Lapland of Finland (latitude 67.4°N), covering a wide range of UV radiation conditions. Since autumn 2005, the sites of the network have been maintaining weathering platforms of specimens of different kinds of polymeric materials. At the same time, the sites have been maintaining their long-term monitoring programmes for spectrally resolved UV radiation. Within UVEMA, these data are used for explaining the differences between the degradation rates of the materials at each site and for correlating the UV conditions in accelerated ageing tests to those under the Sun. We will present the objectives of the UVEMA project aiming at deeper understanding of the ageing of polymers and more reliable assessments for their service life time. Methodologies adopted within the project and the first results of the project will be summarized. © 2009 SPIE.

关键词： Ultraviolet radiation

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Data transmission performance of MIMO precoding over ricean fading channels

Data transmission performance of MIMO precoding over ricean ...

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International Conference on Computer science and Software Engineering, CSSE 2008

作者： Yubin, Shao Chun, Wang Hua, Long Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China National Key Lab for Radar Signal Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780769533360

Transmitter-based linear precoders are considered for downlink multiple input multiple output (MIMO) systems. In this paper, performances of different types of linear precoding are investigated and compared over Ricean fading channels of which the characteristic can be reflect the LOS indoor or outdoor environment. Though out the theory and simulation we reveal that the mean-square errors (MSE) of linear transmit filters are similar as that of the respective receive filters when the transmit symbol and spatially white noise are uncorrelated with an additional constraint of the transmit power. © 2008 IEEE.

关键词： Mean square error

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Distributed autocorrelation-based sequential detection of OFDM signals in cognitive radios

Distributed autocorrelation-based sequential detection of OF...

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3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008

作者： Chaudhari, Sachin Koivunen, Visa Poor, Vincent H. SMARAD CoE Signal Processing Laboratory Helsinki Univ. of Technology Finland School of Engineering and Applied Science Princeton University

ISBN: (纸本)9781424423026

This paper addresses the problem of collaborative spectrum sensing using sequential detection (SD) in cognitive radios. The goal of sequential processing is to reduce the delay and amount of data needed in identifying underutilized spectrum. Each secondary user (SU) employs a simple and computationally efficient autocorrelation-based detector for Orthogonal Frequency Division Multiplexing (OFDM) signals of the primary user (PU). The decision statistics from individual detectors are combined in a fusion center that may be a separate node or one of the secondary users. The statistical properties of the decision statistics are established. The performance of the scheme is studied by theory and simulations. A comparison of the SD scheme with the Neyman-Pearson Fixed Sample Size (FSS) test for the same false alarm and missed detection probabilities is also carried out.

关键词： Autocorrelation

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