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2016 IEEE Chinese Guidance, Navigation and control Conference (IEEE CGNCC2016)

作者： WEN JU JIAOLONG LIU GAOHUA CAI HONGQUAN YUN Pattern Recognition on National Key Laboratory of Science and Technology on Aerospace Intelligence Control Guidance Navigation and Control on National Key Laboratory of Science and Technology on Aerospace Intelligence Control

ISBN: (纸本)9781467383196

Image fusion is one of the main field of multi-source information *** is one of basic features of image,and extracting edges could give a strong support to target *** the edge detection problems,this paper proposes an improved edge detection method based on information ***,through constructing a target function and calculating the differential coefficient of the target function,the mass evaluation of the least target function can be gotten,then the grads matrix of the image is evaluated,and the final edge information can be obtained according to a certain *** algorithm improves the anti-noise quality of edge *** experimental result proves the applicability of the method.

关键词： image Sobel Image An Edge Detection Method Based on Information Fusion

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MRI denoising using randomized version of nonlocal means method

MRI denoising using randomized version of nonlocal means met...

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2016 International Conference on Image Processing, Computer Vision, and pattern recognition, IPCV 2016

作者： Hu, Jinrong He, Jia Fu, Ying Wu, Xi Zhou, Jiliu School of Computer and Soft Engineering Xihua University Chengdu610039 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Chengdu University Chengdu610106 China School of Computer Science Chengdu University of Information Technology Chengdu610225 China

ISBN: (纸本)1601324421

- Non-local mean (NLM) algorithm has been implemented effectively in MRI denoising and is always limited by its computational complexity. To reduce the computational burden of NLM in 3D MRI dataset, in this paper, we used a randomized version of NLM algorithm to remove the noise in MRI data. The random NLM algorithm seeds up the classical NLM by computing a small subset of image patch distances, which are randomly select according to the uniform sampling pattern. Numerical experiments demonstrate that the random NLM can achieve a competitive denoising result at a low sampling rate (0.05) in 3D MRI dataset while reducing the runtime dramatically. © CSREA Press.

关键词： Magnetic resonance imaging

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A MIL-based interactive approach for hotspot segmentation from bone scintigraphy

A MIL-based interactive approach for hotspot segmentation fr...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shijie Geng Jingyang Ma Xiaoguang Niu Shaoyong Jia Yu Qiao Jie Yang Institute of Image Processing and Pattern Recognition The Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781479999897

Bone scintigraphy is widely used to diagnose bone diseases. Accurate hotspot segmentation is a critical task for tumor metastasis diagnosis. In this paper, we propose an interactive approach to detect and extract hotspots in thoracic region based on a new multiple instance learning (MIL) method called EM-MILBoost. We convert the segmentation problem to a multiple instance learning task by constructing positive and negative bags according to the input bounding box. In order to be robust against noisy input, we train a region-level hotspot classifier with EM-MILBoost and develop several segmentation strategies based on it. The experimental results demonstrate that our method outperforms other methods and is robust against various noisy input.

关键词： Image segmentation Noise measurement Bones Training Indexes Belts Standards

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Multi-level thresholding for pupil location in eye-gaze tracking systerm

Multi-level thresholding for pupil location in eye-gaze trac...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Chen, Mo-Han Wen, Jing Zhu, Yu Xing, Hao-Yang Wang, Yi College of Computer Science Chongqing University Chongqing China Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University China Magnetic Resonance Imaging Research Centre Huaxi Hospital Sichuan Chengdu China

ISBN: (纸本)9781509003891

A new pupil location methodis proposed in eye-gaze tracking system. Firstly, input images are enhanced in order to reduce the influence of illumination. Secondly, multiple candidate thresholds are obtained in terms of the valleys in histogram, and then different segmentation results are available. Further, a fusion method based on the overlaps of segmentation results is proposed which acquired candidate regions and the eye region is obtained according to the entropy information of candidate regions. Thirdly, a simple and effective threshold segmentation method based on eye characteristic is employed and pupil area is obtained. Finally, the center of pupil is acquired by ellipse fitting. Experimental results demonstrated that the proposed methods were effective to improve pupil location accuracy. © 2016 IEEE.

关键词： Entropy

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Constructing multi-modality and multi-classifier radiomics predictive models through reliable classifier fusion

arXiv

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arXiv 2017年

作者： Zhou, Zhiguo Zhou, Zhi-Jie Hao, Hongxia Li, Shulong Chen, Xi Zhang, You Folkert, Michael Wang, Jing Department of Radiation Oncology UT Southwestern Medical Center DallasTX United States High-Tech Institute of Xi'an Xi'an China Department of Information and Control Engineering Xi'an University of Technology Xi'an China School of Computer Science and Technology Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China School of Biomedical Engineering Southern Medical Unversity Guangzhou China Institute of Image Processing and Pattern Recognition Xi'an Jiaotong Unversity Xi'an China

Radiomics aims to extract and analyze large numbers of quantitative features from medical images and is highly promising in staging, diagnosing, and predicting outcomes of cancer treatments. Nevertheless, several challenges need to be addressed to construct an optimal radiomics predictive model. First, the predictive performance of the model may be reduced when features extracted from an individual imaging modality (e.g. PET, CT, MRI) are blindly combined into a single predictive model. Second, because many different types of classifiers are available to construct a predictive model, selecting an "optimal" classifier for a particular application is still challenging. In this work, we developed multi-modality and multi-classifier radiomics predictive models that address the aforementioned issues in currently available models. Specifically, a new reliable classifier fusion strategy was proposed to optimally combine output from different modalities and classifiers. In this strategy, modality-specific classifiers were first trained, and an analytic evidential reasoning (ER) rule was developed to fuse the output score from each modality to construct an optimal predictive model. One public datasets and two clinical case studies were performed to validate model performance. The experimental results indicated that the proposed ER rule based radiomics models outperformed the traditional models that rely on a single classifier or simply use combined features from different modalities. Copyright © 2017, The Authors. All rights reserved.

关键词： Diagnosis

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The role of data analysis in the development of intelligent energy networks

arXiv

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arXiv 2017年

作者： Ma, Zhanyu Xie, Jiyang Li, Hailong Si, Zhongwei Zhang, Jianhua Guo, Jun Sun, Qie Pattern Recognition and Intelligent Systems Lab. Beijing University of Posts and Telecommunications Beijing China School of Business Mälardalen University Society and Engineering Västerås Sweden .Tianjin Key Laboratory of Refrigeration Technology School of Mechanical Engineering Tianjin University of Commerce Tianjin China Institute of Thermal Science and Technology Shandong University Ji'nan China Key Laboratory of Universal Wireless Communications Beijing University of Posts and Telecommunications MOE Beijing China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

Data analysis plays an important role in the development of intelligent energy networks (IENs). This article reviews and discusses the application of data analysis methods for energy big data. The installation of smart energy meters has provided a huge volume of data at different time resolutions, suggesting data analysis is required for clustering, demand forecasting, energy generation optimization, energy pricing, monitoring and diagnostics. The currently adopted data analysis technologies for IENs include pattern recognition, machine learning, data mining, statistics methods, etc. However, existing methods for data analysis cannot fully meet the requirements for processing the big data produced by the IENs and, therefore, more comprehensive data analysis methods are needed to handle the increasing amount of data and to mine more valuable information. Copyright © 2017, The Authors. All rights reserved.

关键词： District heating

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An Image Segmentation Algorithm Based on Gray Bit Plane for Flame

An Image Segmentation Algorithm Based on Gray Bit Plane for ...

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2016 4th International Conference on Electrical&Electronics Engineering and Computer Science(ICEEECS 2016)

作者： Xing Deng Jinlan Li Fujian Feng Lin Wang Zhongming Yu School of physics and electronic science Guizhou Normal University Guizhou provincial key laboratory of pattern recognition and intelligent system Liupanshui Normal University

ISBN: (纸本)9781510835429

Flame region judgment is an important part of fire detection system;meanwhile the flame of intelligent monitoring system also has important practical significance to national fire control safety. Therefore, this article puts forward the flame image segmentation method based on gray level bit plane. Firstly, by studying the distribution of flame image in OHTA color space, we found that it can accurately segment the flame area by using the method of the gray level bit plane for component image in OHTA color space. The experiments results show that the algorithm in different scenarios for segmenting flame has a good effectiveness and robustness.

关键词： Fire detect OHTA color space gray bit plane image segmentation

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Brain MRI Segmentation with Patch-based CNN Approach

Brain MRI Segmentation with Patch-based CNN Approach

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第35届中国控制会议

作者： Zhipeng CUI Jie YANG Yu QIAO Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The Key Laboratory of Ministry of Education for System Control and Information Processing

ISBN: (纸本)9781509009107

Brain Magnetic Resonance Image(MRI) plays a non-substitutive role in clinical *** symptom of many diseases corresponds to the structural variants of *** structure segmentation in brain MRI is of great importance in modern medical *** methods were developed for automatic segmenting of brain MRI but failed to achieve desired *** this paper,we proposed a new patch-based approach for automatic segmentation of brain MRI using convolutional neural network(CNN).Each brain MRI acquired from a small portion of public dataset is firstly divided into *** of these patches are then used for training CNN,which is used for automatic segmentation of brain *** results showed that our approach achieved better segmentation accuracy compared with other deep learning methods.

关键词： CNN Deep Learning Brain MRI Segmentation Patch-based

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A robust cell tracking framework by fusing global and local optimization algorithms

A robust cell tracking framework by fusing global and local ...

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第28届中国控制与决策会议

作者： Shu Meng Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467397155

Automated cell tracking is an important branch of multi-object tracking,which can be used for quantitatively analyzing cell migration,proliferation and *** this paper,we proposed a hierarchical tracking method,fusing the global optimal method in consecutive frames assignment and local optimal approach in spatial trajectory *** the process,the detection errors were recognized and cell moving trajectories were completed *** also introduced the concept of clustering to measure the correlation between established short trajectories and reduce the tracking errors caused by fast *** rare information of cells was used in the linkage,the system can work well with *** experimental results show the effectiveness of our approach with cells having different density and activity.

关键词： Multi-object tracking Bipartite graph Optimization Hierarchical tracking

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Objective resolution measurement in single particle reconstructions based on a new spectral signal-to-noise ratio estimation

Objective resolution measurement in single particle reconstr...

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第28届中国控制与决策会议

作者： Shuai Wang Biao Zhang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467397155

The resolution measurement of 3D reconstructed density map in single particle reconstruction is an important and still an open *** this paper,we propose a new protocol to measure the resolution just from the reconstructed density *** approach estimates spectral signal-to-noise ratio(SSNR) of 3D reconstructed map by computing the ratio of signal power to noise power in frequency *** power distributions of signal and noise are estimated from structure particle region and surrounding region segmented by applying a mask *** proposed protocol of calculating SSNR,which we term mask-SSNR(mSSNR),is independent of the reconstruction algorithms and can be used for density maps reconstructed with any reconstruction ***,the mSSNR neither needs to split the dataset into halves like the Fourier shell correlation(FSC) approach,nor any original images or intermediate data like other SSNR calculation methods in this *** mSSNR provides a direct calculation of SSNR based on its original definition,and is proven to be a better approach.

关键词： Electron microscopy Resolution measurement Spectral signal-to-noise ratio Signal processing

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