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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

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TurboPixel with Fuzzy Edge Detection and Multiregional Kernel Graph Cuts for image Segmentation 10

TurboPixel with Fuzzy Edge Detection and Multiregional Kerne...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhang, Qian Xue, Mo-gen Zhou, Pu-cheng Anhui Prov Key Lab Polarized Imaging Detect Techn Hefei Anhui Peoples R China

ISBN: (纸本)9781538619377

Most existing graph cut methods does not perform well for the low-contrast and high-noisy natural images. In this paper, we present an improved image segmentation method based on TurboPixel and kernel graph cuts to solve this problem. The TurboPixel algorithm embedded with fuzzy edge detection is first applied to efficiently pre-segment the original image into homogeneous regions with precise boundary, and these regions are described as superpixels to construct the compact weighted graph. After enhancing the original image, the feature of superpixels is then represented by the Gaussian statistics in the corresponding region to replace the gray level information in the kernel graph cuts model. Additionally, in order to learn the parameters of priori knowledge accurately, we use the kernel fuzzy C-means clustering method to cluster the user interactions in this paper. Finally, considering the image local and non-local information, the energy function in the parametric kernel graph cuts is minimized to achieve the final segmentation. The experimental results demonstrate the feasibility and superiority of the proposed method in this paper.

关键词： superpixels turbopixels kernel fuzzy C-means clustering kernel metric Kernel Graph Cuts image segmentation

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Research on image Retrieval Based on the Convolutional Neural Network 10

Research on Image Retrieval Based on the Convolutional Neura...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Chen, Chaoyi Li, Xiaoqi Zhang, Bin BUPT Pattern Recognit & Intelligent Syst Lab Beijing 100876 Peoples R China BUPT Sch Informat & Commun Engn Beijing 100876 Peoples R China

ISBN: (纸本)9781538619377

The development of the Internet has led to the accumulation of a large number of images in various databases. People are eager to find useful information in these databases which stimulate the development of image retrieval technologies. In this paper, we mainly study image retrieval based on the convolutional neural network. The study is divided into four parts to explore characteristics of convolution neural networks used in image retrieval. The first part introduces the structure of the convolutional neural network and the method of extracting features from images. The second part compares the effects of different similarity measures on retrieval accuracy. The third part studies the way to speed up retrieval. We use PCA to reduce feature dimensions and draw a line chart of dimension and accuracy. Then we analyze the reason why the change of accuracy rate is divided into two stages: ascending first and descending later. The fourth part studies the way to increase retrieval accuracy. We compare the retrieval accuracy before and after fine-tuning and analyze the reasons for that. In the end, we sum up the whole text and summarize key points that we should consider when designing an image retrieval system based on the convolutional neural network.

关键词： image retrieval convolutional neural network dimension reduction network fine-tuning

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Decomposition of tensors of cardio-vascular signals using CANDECOMP/PARAFAC algorithms 10

Decomposition of tensors of cardio-vascular signals using CA...

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10th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2017

作者： Almirantearena, Fernando Nuno Department of Electronics and Computer Science Faculty of Engineering Mar del Plata Argentina

ISBN: (纸本)9781538619377

In the processing of biological signals of the electrocardiogram (ECG) and Arterial Diameter Variation (ADV) there are several methods for the extraction of cardiovascular event characteristics. In this case, the canonical polyadic decomposition of CANDECOMP/PARAFAC (CP) tensors is used in the processing of the mixed signals of ECG-ADV;the ECG-ADV signals are extracted from each patient simultaneously and the detection quality of the ECG complex is verified. To do this, the ECG complex and the systolic wave of the ADV wave are aligned with Gaussian noise, and then the tensors were constructed for both signals. Five algorithms of CP were applied and the quality of the factorization of each one of the algorithms was checked with four indices. Both signals were shown to be non-collinear, and the algorithms that have the minimum number of iterations at the convergence were determined. © 2017 IEEE.

关键词： Electrocardiograms

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C-arm based image-guided Percutaneous Puncture of Minimally Invasive Spine Surgery 10

C-arm based Image-guided Percutaneous Puncture of Minimally ...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Li, Yang Liang, Wei An, Haibo Zhang, Yinlong Tan, Jindong Chinese Acad Sci Shenyang Inst Automat Key Lab Networked Control Syst Shenyang 110016 Liaoning Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Tennessee Dept Mech Aerosp & Biomed Engn Knoxville TN 37996 USA

ISBN: (纸本)9781538619377

Percutaneous Puncture is the first step of minimally invasive spine surgery and has a great visual problem. Although the augmented reality methods are able to deal with the visualization challenge, these methods still utilize artificial patterns as alignment markers to implement virtual-actual merging. Occlusion, shift and damage of these artificial markers will lead to failure of navigation. Therefore, this paper presents a novel framework of augmented reality navigation for percutaneous puncture. We redesign the mobile C-arm with RGB industrial camera. The feature points of lumbar vertebra image are applied as natural markers to achieve augmented reality. We integrate the preoperative 3D model, intraoperative 2D X-ray image and intraoperative 3D scene to provide a straightforward and seamless navigation. Preliminary experiments are conducted on spine phantom in box. The qualitative and quantitative experimental results show that our proposed method performs more accuracy navigation for entry-point localization than another state-of-the-art method.

关键词： C-arm image-guided calibration registration augmented reality

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A Gradient-Domain image Enhancement Method for Traffic Signs in Nighttime Surveillance 10

A Gradient-Domain Image Enhancement Method for Traffic Signs...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Wang, Simin Li, Xiaoguang Zhang, Hui Zhuo, Li Beijing Univ Technol Signal & Informat Proc Lab Beijing Peoples R China

ISBN: (纸本)9781538619377

Nighttime video surveillance may suffer from non-uniform illumination from artificial light sources. Meanwhile, these light sources which often result in so noticeable amounts of glow that the objects nearby the light sources cannot be seen at all. To solve the above problem, our paper proposed a novel gradient-domain image enhancement method for traffic signs in nighttime surveillance. We found that both of the glow-removal and image fusion can be represented as a kind of gradient adjustment. Therefore, in our method, remove the glow effects via image gradient decomposition at first. Then, complementary details of inter frames can be fused together in the gradient domain. Finally, the enhanced image will be obtained via a Poisson solver. We have done many experiments and the results show that the proposed method can effectively enhance the traffic signs in nighttime traffic videos.

关键词： image enhancement nighttime traffic surveillance traffic signs gradient domain fusion

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Feature Extraction and Classification of Xinjiang High Morbidity Esophageal Cancer Based on Tamura and Wavelet Transform

Feature Extraction and Classification of Xinjiang High Morbi...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Pazilya Yusantay Juan Yao Chuan Bo Yan Abdugheni Kutluk Murat Hamit Wei Liu School of Basic Medicine Xinjiang Medical University Urumqi China Department of Radiology First Affiliated Hospital Xinjiang Medical University Urumqi China College of Medical Engineering Technology Xinjiang Medical University Urumqi China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China

Goal: The incidence of esophageal cancer in Xinjiang is remaining obstinately high. In order to improve the accuracy and efficiency of esophageal cancer diagnosis, this paper discusses the techniques and methods involved in the computer-aided diagnosis of esophageal carcinoma, which also to provide evidence for early detection, diagnosis and treatment of esophageal cancer. Methods: Selected normal esophagus, mushroom esophageal carcinoma, constricted esophageal carcinoma and ulcerative esophageal carcinoma, each 100 pieces and the regions of interest (ROI) were segmented manually. Then extracted texture features based on Wavelet Transform (WT) and Tamura algorithm and constructed Support Vector Machine (SVM) and BP Neural Network classifier to classify these features. Results: A total of 26 dimensional features were extracted from each image. The best classification accuracy of normal esophagus, mushroom esophageal carcinoma and ulcerative esophageal carcinoma reached 98.667%; It was 95.667% for normal esophagus, constricted esophageal carcinoma and ulcerative esophageal carcinoma; And 87.667% for normal esophagus, mushroom esophageal carcinoma and constricted esophageal carcinoma; 89.25% when classified normal esophagus and three kinds of advanced esophageal carcinoma. The classification efficiency of comprehensive features which consist of Tamura and WT features was better than that of single Tamura or WT feature. The Classification performance of SVM was superior to BP neural network. Conclusion: In this study, texture features based on Tamura and WT were extracted and classified by SVM and BP neural network classifier from ROI of normal esophagus and three kinds of advanced esophageal carcinoma. Results show that the classification accuracy of this study is high, which lays a foundation for the development of computer aided diagnosis system for esophageal carcinoma.

关键词： Cancer Feature extraction Support vector machines Esophagus Medical diagnostic imaging Neural networks

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Single-image Super-Resolution based on Regularization with Stationary Gradient Fidelity 10

Single-Image Super-Resolution based on Regularization with S...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Yu, Lejun Cao, Siming He, Jun Sun, Bo Dai, Feng Beijing Normal Univ Coll Informat Sci & Technol Beijing 100875 Peoples R China Chinese Acad Sci Inst Comp Technol Beijing 100191 Peoples R China

ISBN: (纸本)9781538619377

Single-image super-resolution, reconstructing a high resolution (HR) image from a low resolution (LR) one, is an ill-posed problem. Regularization, a method for ill-posed problem, is widely used in super-resolution. The definition of the fidelity term in regularization energy is a key to the performance of regularization based super-resolution. Traditional fidelity is defined as the energy of error image between down-sampled version of HR image estimated and the observed LR image. Since the mpixels not in sampled positions are not considered, the gradient of traditional fidelity is non-stationary. To avoid this problem in traditional fidelity, we propose to define the fidelity term as the energy of error image between the estimated HR image estimate and its blurred version. When gradient decent is used to optimize the regularization energy, we propose an error interpolation fidelity gradient (EIFG) method to estimate a stationary gradient of proposed fidelity. Compared with other methods, experimental results show that our method improve both qualitative and quantitative performances of reconstructed HR image.

关键词： super-resolution ill-posed problem regularization fidelity stationary gradient

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Artificial Object Edge Detection based on Enhanced Canny Algorithm for High-speed Railway Apparatus Identification 10

Artificial Object Edge Detection based on Enhanced Canny Alg...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Ma, Qianli D. Y. Ma, Zhen Ji, Changjuan Yin, Kai Zhu, Ting Bian, Chunhua Nanjing Univ Posts & Telecommun Sch Geog & Biol Informat Nanjing Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Coll Telecomm & Informat Engn Nanjing Jiangsu Peoples R China Shanghai Railway Bur Inst Sci & Technol Shanghai Peoples R China Nanjing Univ Sch Elect Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538619377

In computer vision, artificial object identification usually is the central task, and edge detection is the most utilized method. In this paper, an enhanced Canny algorithm is used for artificial object edge detection, in order to suppress the influence of noise on image edge detection and edges from extraneous objects. The algorithm first uses adaptive smoothing filtering to filter out salt-and-pepper noise, which can better protect the details of the image. Then, the geometric characteristics of edge is used to distinguish between edges from artificial apparatus and extraneous objects. Experiments on images obtained in highspeed railway filed survey show that the enhanced algorithm can accurately locate the edge of apparatus, and can effectively suppress the edges caused by noise, ballast and texture on the surface of objects, compared with the traditional Canny edge detection algorithm.

关键词： Dynamic Edge detection Canny operator Adaptive thresholds image noise geometric feature

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Mapping Quasi-circular Vegetation Patches Using QuickBird image with an Object-based Approach 10

Mapping Quasi-circular Vegetation Patches Using QuickBird Im...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Liu, Qingsheng Liang, Li Liu, Gaohuan Huang, Chong Li, He Zhao, Jun Chinese Acad Sci IGSNRR State Key Lab Resources & Environm Informat Syst Beijing Peoples R China Off Dongying Municipal Govt Dongying Peoples R China

ISBN: (纸本)9781538619377

Data at vegetation patch scale have always been needed for remote sensing researches, but scholars have instead used the coarser scale data because of limitations of image spatial resolution and information extraction approach. This paper provides a preliminary assessment of an object-based approach with 0.6 m Ortho-rectification QuickBird high spatial resolution multispectral image for detecting automatically the location and areas of the quasi-circular vegetation patches as they grow upon the abandoned land and tidal flat in the Yellow River Delta (YRD), China. The quasi-circular vegetation patches detected from our methods produced a good correlation with the counts identified via comparable visual interpretation on the Quickbird high spatial resolution image with the precision rate 85.1% and F 0.802. This approach has considerable potential for monitoring the long-term quasi-circular vegetation patch dynamics using high spatial resolution imagery.

关键词： quasi-circular vegetation QuickBird image multi-scale segmentation Yellow River Delta

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Batch images Compression Algorithm Based on the Common Features 10

Batch Images Compression Algorithm Based on the Common Featu...

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10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Wang, Zhiqiong Lin, Zhixiang Xu, Lining Zhao, Yue Xin, Junchang Northeastern Univ Sino Dutch Biomed & Informat Engn Sch Shenyang 110169 Liaoning Peoples R China Northeastern Univ Sch Comp Sci & Engn Shenyang 110169 Liaoning Peoples R China

ISBN: (纸本)9781538619377

Medical images take up huge data space and have slow transmission speed. Medical images have high cost of transmission and take up width channel. image compression can speed up the transmission of medical images and save up the cost of transmission. They make doctors' diagnosis convenient. The ratio of compression sensing is very slow and the error of the reconstructed images is great. In this study we propose a compressed sensing algorithm based on common features. We use 10 Computed Tomography(CT) images of thoracic cavity and 2 Magnetic Resonance Imaging(MRI) images of heart to proof the result. According to the results, the algorithm is effective in compression and reconstruction. The algorithm has 6.4% improvement in peak signal-to-noise ratio, 100% improvement in compression ratio and the average error has reduced. Accordingly, the algorithm based on common characteristic have more advantages in compression and reconstruction.

关键词： image coding image reconstruction Heuristic algorithms Medical diagnostic imaging Matching pursuit algorithms Mutual information

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