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

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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SIMULTANEOUS ACCURATE DETECTION OF PULMONARY NODULES AND FALSE POSITIVE REDUCTION USING 3D CNNS

SIMULTANEOUS ACCURATE DETECTION OF PULMONARY NODULES AND FAL...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Yulei Qin Hao Zheng Yue-Min Zhu Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University 800 Dongchuan RD. Minhang District Shanghai China University Lyon INSA Lyon CNRS Inserm CREATIS UMR 5220 U1206 F-69621 France

ISBN: (纸本)9781538646595

Accurate detection of nodules in CT images is vital for lung cancer diagnosis, which greatly influences the patient's chance for survival. Motivated by successful application of convolutional neural networks (CNNs) on natural images, we propose a computer-aided diagnosis (CAD) system for simultaneous accurate pulmonary nodule detection and false positive reduction. To generate nodule candidates, we build a full 3D CNN model that employs 3D U-Net architecture as the backbone of a region proposal network (RPN). We adopt multi-task residual learning and online hard negative example mining strategy to accelerate the training process and improve the accuracy of nodule detection. Then, a 3D DenseNet-based model is presented to reduce false positive nodules. The densely connected structure reuses nodules' features and boosts feature propagation. Experimental results on LUNA16 datasets demonstrate the superior effectiveness of our approach over state-of-the-art methods.

关键词： Pulmonary nodule detection computer-aided diagnosis false positive reduction Diagnosis, Computer-Assisted nodules nodule nodules Root nodules False False-positives Concurrency

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ERP based decision fusion for AD diagnosis across cohorts

ERP based decision fusion for AD diagnosis across cohorts

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

作者： Metin Ahiskali Deborah Green John Kounios Christopher M. Clark Robi Polikar Signal Processing and Pattern Recognition Laboratory Department of Electrical and Computer Engineering Rowan University Glassboro NJ USA Department of Psychology Drexel University Philadelphia PA USA Department of Neurology University of Pennsylvania Philadelphia PA USA

As the average life expectancy increases, particularly in developing countries, prevalence of neurodegenerative diseases has also increased. This trend is especially alarming for Alzheimer's disease (AD); as there is no cure to stop or reverse the effects of AD. However, recent pharmacological advances can slow the progression of AD, but only if AD is diagnosed at early stages. We have previously introduced an ensemble of classifiers based approach for combining event related potentials obtained from different electrode locations as an effective approach for early diagnosis of AD. We further expand this approach and analyze its robustness and stability in two ways: comparing the diagnostic accuracy on hand selected and cleaned data vs. standard automated preprocessing, but more importantly, comparing the diagnostic accuracy on two different cohorts, whose data are collected under different settings: a research university lab and a community clinic.

关键词： Enterprise resource planning Proteins Biomedical signal processing Hospitals Alzheimer's disease Electrodes Robust stability Medical diagnostic imaging Biomarkers Electroencephalography

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Ensemble Based Data Fusion from Parietal Region Event Related Potentials for Early Diagnosis of Alzheimer's Disease

Ensemble Based Data Fusion from Parietal Region Event Relate...

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International Joint Conference on Neural Networks (IJCNN)

作者： Brian A. Balut Matthew T. Karnick Deborah Green John Kounios Christopher M. Clark Robi Polikar Signal Processing and Pattern Recognition Laboratory of the Electrical and Computer Engineering Department Rowan University Glassboro NJ USA Department of Psychology Drexel University Philadelphia PA USA Department of Neurology University of Pennsylvania Philadelphia PA USA

As a natural consequence of steady increase of average population age in developed countries, Alzheimer's disease is becoming an increasingly important public health concern. The financial and emotional toll of the disease is exacerbated with lack of standard diagnostic procedures available at the community clinics and hospitals, where most patients are evaluated. In our recent preliminary results, we have reported that the event related potentials (ERPs) of the electroencephalogram can be used to train an ensemble-based classifier for automated diagnosis of Alzheimer's disease. In this study, we present an updated alternative approach by combining complementary information provided by ERPs obtained from several parietal region electrodes. The results indicate that ERPs obtained from parietal region of the cortex carry substantial complementary diagnostic information. Specifically, the diagnostic ability of such an approach is substantially better, compared to the performance obtained by using data from any of the individual electrodes alone. Furthermore, the diagnostic performance of the proposed approach compares very favorably to that obtained at community clinics and hospitals.

关键词： Alzheimer's disease Enterprise resource planning Hospitals Electrodes Senior citizens Biomarkers Protocols Delay Neural networks USA Councils

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EEG and MRI data fusion for early diagnosis of Alzheimer's disease

EEG and MRI data fusion for early diagnosis of Alzheimer's d...

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

作者： Tejash Patel Robi Polikar Christos Davatzikos Christopher M. Clark Signal Processing and Pattern Recognition Laboratory of the Electrical and Computer Engineering Department Rowan University Glassboro NJ USA Department of Radiology University of Pennsylvania Philadelphia PA USA Department of Neurology University of Pennsylvania Philadelphia PA USA

The prevalence of Alzheimer's disease (AD) is rising alarmingly as the average age of our population increases. There is no treatment to halt or slow the pathology responsible for AD, however, new drugs are promising to reduce the rate of progression. On the other hand, the efficacy of these new medications critically depends on our ability to diagnose AD at the earliest stage. Currently AD is diagnosed through longitudinal clinical evaluations, which are available only at specialized dementia clinics, hence beyond financial and geographic reach of most patients. Automated diagnosis tools that can be made available to community hospitals would therefore be very beneficial. To that end, we have previously shown that the event related potentials obtained from different scalp locations can be effectively used for early diagnosis of AD using an ensemble of classifiers based decision fusion approach. In this study, we expand our data fusion approach to include MRI based measures of regional brain atrophy. Our initial results indicate that ERPs and MRI carry complementary information, and the combination of these heterogeneous data sources using a decision fusion approach can significantly improve diagnostic accuracy.

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Estimating the Connection Probability for 2-D Mesh Networks by Monte Carlo Methods

Estimating the Connection Probability for 2-D Mesh Networks ...

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International Conference on Computer and Management (CAMAN)

作者： Meilian Liang Binmei Liang Zehui Shao Xiaodong Xu School of Mathematics and Information Science Guangxi University Nanning China Key Laboratory of Pattern Recognition and Intelligent Information Processing School of Information Science & Technology University of Chengdu Chengdu China Guangxi Academy of Sciences Nanning China

Fault tolerance is a central issue in the design and implementation of interconnection networks for large parallel systems. Connection probability of a network is a good network fault tolerance measure. For a mesh of given size and node failure probability, the gap between the known upper and lower bounds on the connection probability is often very large. In this paper we design algorithms to estimate the connection probability for 2-D meshes by Monte Carlo methods. The experiment is carefully designed and performed, and the simulation results give good estimates of the connection probability for 2-D meshes and can be used to evaluate the known lower and upper bounds on connection probability for 2-D meshes.

关键词： Mesh networks Fault tolerance Fault tolerant systems Upper bound Monte Carlo methods Computers Simulation

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Handwritten Chinese character segmentation using a two-stage approach

Handwritten Chinese character segmentation using a two-stage...

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International Conference on Document Analysis and recognition

作者： Shuyan Zhao Zheru Chi Pengfei Shi Qing Wang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Centre for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Computer Science and Engineering Northwestern Polytechnical University Xi'an China

ISBN: (纸本)0769512631

Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage approach is addressed to segment unconstrained handwritten Chinese character strings. A string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. At the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. Geometric features are extracted and fuzzy decision rules learned from examples are used to evaluate the segmentation paths. By using this two-stage segmentation approach, we can achieve both good performance and efficiency in segmenting unconstrained handwritten Chinese characters.

关键词： image segmentation Character recognition pattern recognition Handwriting recognition Signal processing image processing Computer science Electronic mail image recognition Skeleton

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Adaptive dynamic loading and unloading mechanism applied to development environment for image processing algorithm

Adaptive dynamic loading and unloading mechanism applied to ...

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2011 International Conference on Computer Science and Service System, CSSS 2011

作者： Lu, Haifeng Zhang, Tianxu Yan, Wei Cheng, Zhao State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Department of Technology Hubei Daily Media Group Wuhan 430077 China

ISBN: (纸本)9781424497638

An advanced development environment contributes to research process greatly. This paper presents a novel adaptive dynamic loading and unloading mechanism applied to development environment for image processing algorithm and two implementation methods of the mechanism. Based on the inherent characteristic of variable arguments of functions in programming language and explicit linking technique for dynamic link library (DLL), the mechanism is to integrate the image processing algorithm into the DLL file which is independent from the development environment, and to make the development environment identify the normative algorithm DLL and load functions of image processing algorithm successfully when needed. The proposed mechanism has been implemented in a development environment written by C/C++ language. The results show that the development environment based on the novel mechanism can improve work efficiency by making researchers only focus on the development of image processing algorithm rather than the other inefficient and repetitive work. At the same time the standardability, reusability and confidentiality of image processing algorithm can be promoted greatly. This mechanism is also applicable to other similar systems. © 2011 IEEE.

关键词： Reusability

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Mixed one-bit compressive sensing with application to overexposure correction for CT reconstruction

arXiv

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arXiv 2017年

作者： Huang, Xiaolin Xia, Yan Shi, Lei Huang, Yixing Yan, Ming Hornegger, Joachim Maier, Andreas Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Radiology Stanford University CA United States School of Mathematical Sciences Fudan University Shanghai China Pattern Recognition Lab of Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Computational Mathematics Science and Engineering Michigan State University MI United States

When a measurement falls outside the quantization or measurable range, it becomes saturated and cannot be used in classical reconstruction methods. For example, in C-arm angiography systems, which provide projection radiography, fluoroscopy, digital subtraction angiography, and are widely used for medical diagnoses and interventions, the limited dynamic range of C-arm flat detectors leads to overexposure in some projections during an acquisition, such as imaging relatively thin body parts (e.g., the knee). Aiming at overexposure correction for computed tomography (CT) reconstruction, we in this paper propose a mixed one-bit compressive sensing (M1bitCS) to acquire information from both regular and saturated measurements. This method is inspired by the recent progress on one-bit compressive sensing, which deals with only sign observations. Its successful applications imply that information carried by saturated measurements is useful to improve recovery quality. For the proposed M1bit-CS model, alternating direction methods of multipliers is developed and an iterative saturation detection scheme is established. Then we evaluate M1bit-CS on one-dimensional signal recovery tasks. In some experiments, the performance of the proposed algorithms on mixed measurements is almost the same as recovery on unsaturated ones with the same amount of measurements. Finally, we apply the proposed method to overexposure correction for CT reconstruction on a phantom and a simulated clinical image. The results are promising, as the typical streaking artifacts and capping artifacts introduced by saturated projection data are effectively reduced, yielding significant error reduction compared with existing algorithms based on extrapolation. Copyright © 2017, The Authors. All rights reserved.

关键词： Compressed sensing

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New design for 9/7-tap wavelet filter and its VLSI implementation

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Jisuanji Xuebao/Chinese Journal of Computers 2008年第3期31卷 411-418页

作者： Tian, Xin Tan, Yi-Hua Tian, Jin-Wen State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Wuhan 430074 China

This paper designs a new kind of lifting 9-7-tap wavelet filter with binary characteristics and presents a high speed VLSI structure for the wavelet filter. The coefficients of the lifting filters are binary numbers, so it can simplify the VLSI design. The test results for compression performances have shown that the new filter is good almost as CDF97 under PSNR. when the data has a finite accuracy, it may have a better performance than CDF97. The filter can be implemented with using adders and shifters. Therefore the hardware resources can be saved and the critical path can be shortened. According to using the folding technology and the retiming technology, the architecture of the design can be transformed into a kind of embedded folding architecture which leads to the parallel computation of addition operations. So the critical path can be shortened to nearly the time of a addition operation and the utilization of the hardware resources also has a good performance. Simulation results show that the max working frequency could almost reach 250 MHz which is the four times by the CDF97;The occupied logic cell is reduced by 66.7 compared with the CDF97+4 stages pipeline. So it is especially suitable for the high speed VLSI design.

关键词： VLSI circuits

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