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New image correlation analysis based on fuzzy information gain

Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University 2006年第3期40卷 466-470页

作者： Shen, Hong-Bin Yang, Jie Liu, Xiao-Jun Chen, Ning-Jiang Inst. of Image Processing and Pattern Recognition Shanghai Jiaotong Univ. Shanghai 200240 China Philips Research East Asia Shanghai 200070 China

Based on the statistic and the fuzzy uncertainty information in an image, a new fuzzy information gain method was proposed to measure the distinctness between the object image and the reference image, which provides a new criterion for image matching or retrieval. The experimental results demonstrate the effectiveness of the new method.

关键词： image processing

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AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networks

arXiv

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arXiv 2019年

作者： Qin, Yulei Chen, Mingjian Zheng, Hao Gu, Yun Shen, Mali Yang, Jie Huang, Xiaolin Zhu, Yue-Min Yang, Guang-Zhong Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Insa Lyon Lyon France Hamlyn Centre for Robotic Surgery Imperial College London London United Kingdom

Airway segmentation on CT scans is critical for pulmonary disease diagnosis and endobronchial navigation. Manual extraction of airway requires strenuous efforts due to the complicated structure and various appearance of airway. For automatic airway extraction, convolutional neural networks (CNNs) based methods have recently become the stateof-the-art approach. However, there still remains a challenge for CNNs to perceive the tree-like pattern and comprehend the connectivity of airway. To address this, we propose a voxel-connectivity aware approach named AirwayNet for accurate airway segmentation. By connectivity modeling, conventional binary segmentation task is transformed into 26 tasks of connectivity prediction. Thus, our AirwayNet learns both airway structure and relationship between neighboring voxels. To take advantage of context knowledge, lung distance map and voxel coordinates are fed into AirwayNet as additional semantic information. Compared to existing approaches, AirwayNet achieved superior performance, demonstrating the effectiveness of the network's awareness of voxel connectivity. Copyright © 2019, The Authors. All rights reserved.

关键词： Computerized tomography

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Progressive low/high-resolution Space Attention Fusion Network for Single image Super-Resolution

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Journal of Physics: Conference Series 2021年第1期1828卷

作者： Chengzu Zhong Yue Zhou Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

The general single image super-resolution methods mainly extract features from the high-resolution (HR) space by the pre-upscaling step at the beginning of the network or from the low-resolution (LR) space before the post-upscaling step at the end of the network. The former way requires high computation as well as misleading the network by wrong artificial priors. The latter way cannot learn mapping well by only conducting simple operations in HR space. In this paper, we aim to utilize the features from LR and HR space more efficiently and propose the novel network, which applies a frequency-slicing mechanism to divide features into LR and HR space, a direction-aware fusion residual group to extract distinctive features in LR space and an attention fusion module to recalibrate features in HR space. The experimental results demonstrate that our model is superior to the state-of-the-art methods upon quantitative metrics and visual quality.

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Prediction of protein folding rates from structural topology and complex network properties

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IPSJ Transactions on Bioinformatics 2010年 3卷 40-53页

作者： Song, Jiangning Takemoto, Kazuhiro Shen, Hongbin Tan, Hao Gromiha, M. Michael Akutsu, Tatsuya Bioinformatics Center Institute for Chemical Research Kyoto University Japan Department of Biochemistry and Molecular Biology Monash University Australia PRESTO Japan Science and Technology Agency Japan Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Computational Biology Research Center National Institute of Advanced Industrial Science and Technology Japan

As a fundamental biological problem, revealing the protein folding mechanism remains to be one of the most challenging problems in structural bioinformatics. Prediction of protein folding rate is an important step towards our further understanding of the protein folding mechanism and the complex sequencestructure-function relationship. In this article, we develop a novel approach to predict protein folding rates for two-state and multi-state protein folding kinetics, which combines a variety of structural topology and complex network properties that are calculated from protein three-dimensional structures. To take into account the specific correlations between network properties and protein folding rates, we define two different protein residue contact networks, based on two different scales Protein Contact Network (PCN) and Long-range Interaction Network (LIN) to characterize the corresponding network features. The leave-one-out cross-validation (LOOCV) tests indicate that this integrative strategy is more powerful in predicting the folding rates from 3D structures, with the Pearson's Correlation Coefficient (CC) of 0.88, 0.90 and 0.90 for two-state, multi-state and combined protein folding kinetics, which provides an improved performance compared with other prediction work. This study provides useful insights which shed light on the network organization of interacting residues underlying protein folding process for both two-state and multi-state folding kinetics. Moreover, our method also provides a complementary approach to the current folding rate prediction algorithms and can be used as a powerful tool for the characterization of the foldomics protein data. The implemented webserver (termed PRORATE) is freely accessible at http://***/~sjn/folding/. © 2010 Information processing Society of Japan.

关键词： Forecasting

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Needle Segmentation Using 3D Quick Randomized Hough Transform

Needle Segmentation Using 3D Quick Randomized Hough Transfor...

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International Workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Wu Qiu Mingyue Ding Ming Yuchi Institute for Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China Department of Biomedical Engineering School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D quick randomized Hough transform (3DGHT), which is based on the 3D randomized Hough transform and coarse-fine searching strategy. We tested it with water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1 degree and position deviation less than 1 mm, and the computational time of segmentation with 35 MB data is within 1s.

关键词： Needles image segmentation Electrodes Ultrasonic imaging Intelligent networks Artificial intelligence Educational technology Hemorrhaging Imaging phantoms Radio frequency

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Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segmentation Review

Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segme...

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International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Xin Yang Jiaoying Jin Ming Yuchi Mingyue Ding State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Huazhong University of Science and Technology HUST Wuhan Hubei China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology HUST Wuhan Hubei China

Stroke and heart attack, which could be led by a kind of cerebrovascular and cardiovascular disease named asatherosclerosis, would seriously cause human morbidity and mortality. And the carotid artery of intima-media thickness (IMT) is a key indicator to the disease. With the development of computer assisted diagnosis (CAD) technology, Ultrasound imaging, being real-time, economic, reliable, safe, and now seems to become a standard in vascular assessment methodology especially for the measurement of IMT. This review is an attempt to discuss the clinical relevance of measurements in clinical practice at first, and then followed by the challenges that one has to face when approaching the segmentation of ultrasound images. Secondly, the paper is presentation of common used methods for the IMT segmentation and measurement. An overview of summary and future perspectives is given in conclusion finally.

关键词： Ultrasonic imaging image segmentation Carotid arteries Ultrasonic variables measurement Biomedical imaging

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Robot Debater: Debate-styled Text Auto-generation System Based on Large Foundation Language Models

Robot Debater: Debate-styled Text Auto-generation System Bas...

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pattern recognition and Machine Learning (PRML), IEEE International Conference on

作者： Yu Zhu Yijun Ling Xufeng Ling Jie Yang Shanghai Library (Institute of Scientific and Technical Information of Shanghai) Shanghai China Shanghai Xiangming High School Shanghai China School of Artificial Intelligence Shanghai Normal University Tianhua College Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

We use a large foundation language model, which is fine-tuned with debate corpora, to develop a robot debater application. To address the limitations of requiring immense computational power in large base language models, this study takes advantage of the Low Rank Adaption characteristic prevalent in domain expert knowledge. By applying Low Rank Adaption technology and fine-tuning with a dedicated dataset, the computational load is reduced to just one-thousandth of what is needed for a large language model, greatly expanding the application scenarios of robot debaters using large language models. In view of the characteristics of debate competitions, this model can preset a variety of debate scenarios and supports personalized debate processes. It employs intelligent voice recognition technology combined with a multi-channel voice input method, allowing for precise localization of different human debaters and improving the accuracy of voice input recognition. The system can support multiple large-scale language generation models and utilize various different voice broadcasting systems, including male and female voice styles, as well as a range of voice emotions. This model can be applied to debate competitions held in universities, high schools, and various industries. It can support human-machine debates as well as machine-to-machine debates.

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A hybrid method to segment common carotid arteries from 3D ultrasound images

A hybrid method to segment common carotid arteries from 3D u...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Xin Yang Wanji He Jiaoying Jin Xuming Zhang Ming Yuchi Mingyue Ding State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Huazhong University of Science and Technology Wuhan Hubei China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China S School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

A hybrid method is used to evaluate atherosclerosis through a mathematical morphology approach and GVF-Snake method. Common carotid artery (CCA) segmentation requires outlining the intima and adventitia contours on the transverse view of B-mode ultrasound (US) images. The lumen and adventitia contours are segmented using a morphology and GVF-Snake methods, respectively. Upon analyzing ten separate patient data sets demonstrate that a comparison between the proposed method and the traditional approach (manual contouring) on 110 transverse images of the CCA showed a mean absolute distance (MAD) of 0.67±0.17mm for lumen and 0.64 ± 0.19mm for adventitia. Their Dice Similarity Coefficient (DSC) values are 92.7%±2.3% and 90.3%±3.5% for lumen and adventitia segmentation, respectively. These values are in good agreement with clinical standards.

关键词： image segmentation Three dimensional displays Measurement Biomedical imaging Ultrasonic imaging Sun

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Automatic Detection of the Intima-Media Layer in Ultrasound Common Carotid Artery image Based on Active Contour Model

Automatic Detection of the Intima-Media Layer in Ultrasound ...

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International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Jiaoying Jin Mingyue Ding Xin Yang Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Life School of Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI) Life School of Science and Technology Huazhong University of Science and Technology Wuhan China

The analysis of the carotid artery wall is of paramount importance in clinical practice. Especially, the intima-media thickness is a risk index for some of the most severe acute cerebrovascular pathologies, hence, an accurate segmentation of the different layers of the carotid artery is needed. IMT is usually manually measured on longitudinal B-mode ultrasound images. In the past ten years, many computer-based techniques for intima-media thickness measurement have been proposed to overcome the limits of manual segmentation, but almost all of them require a certain degree of user interaction. In this paper we proposed a novel approach for the completely user-independent segmentation of the common carotid artery wall. Our algorithm is designed for the extraction of the intima and media layers of the distal carotid wall in ultrasound images. It is based on integrated approach consisting of common carotid artery region identification, contour initialization with threshold segmentation, intima-lumen segmentation with Snake, and media-adventitia segmentation with GVF-Snake that enables the automated tracing of the carotid walls. The acoustic impedance's difference is employed to locate common carotid artery region. Finally, the characterization of the algorithm in terms of segmentation error was evaluated with a set of 40 common carotid artery ultrasound images and compared to the segmentation traced by a trained operator. Experiments showed that a mean error lower than 1.3 pixel both on the intima and media layers was obtained, which is comparable to that obtained by means of operator dependent techniques.

关键词： image segmentation Carotid arteries Ultrasonic imaging Media Algorithm design and analysis Ultrasonic variables measurement

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Fast signal recovery from saturated measurements by linear loss and nonconvex penalties

arXiv

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arXiv 2018年

作者： He, Fan Huang, Xiaolin Liu, Yipeng Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The MOE Key Laboratory of System Control and Information Processing Shanghai200240 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The Department of Computational Mathematics Science and Engineering Michigan State University MI United States

Sign information is the key to overcoming the inevitable saturation error in compressive sensing systems, which causes information loss and results in bias. For sparse signal recovery from saturation, we propose to use a linear loss to improve the effectiveness from existing methods that utilize hard constraints/hinge loss for sign consistency. Due to the use of linear loss, an analytical solution in the update progress is obtained, and some nonconvex penalties are applicable, e.g., the minimax concave penalty, the 0 norm, and the sorted 1 norm. Theoretical analysis reveals that the estimation error can still be bounded. Generally, with linear loss and nonconvex penalties, the recovery performance is significantly improved, and the computational time is largely saved, which is verified by the numerical experiments. Copyright © 2018, The Authors. All rights reserved.

关键词： Compressed sensing

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