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SEGMENTATION OF RANGE image BASED ON KOHONEN NEURAL NETWORK

Journal of Electronics(China) 2001年第3期18卷 237-241页

作者： Zou Ning Liu Jian Zhou Manli Li Qing(State Education Commission Res. lab. for image Processing & Intelligent Control. Electronic & Information Engineering Dept., Huazhong University of science & technology. Wuhan 430074) State Education Commission Res. Lab. for Image Processing & Intelligent Control Electronic & Information Engineering Dept. Huazhong University of Science & Technology Wuhan

This paper presents an unsupervised range image segmentation based on Kohonen neural network. At first, the derivative and partial derivative of each point are calculated and the normal in each points is gotten. With the character vectors including normal and range value, self-organization map is introduced to cluster. The normal analysis is used to eliminate over-segmentation and the last result is gotten. This method avoid selecting original seeds and uses fewer samples, moreover computes rapidly. The experiment shows the better performance.

关键词： Range image Segmentation Kohonen neural network Merge

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Selection of Cancer Biomarkers from Microarray Gene Expression Data Utilizing the Bi-Objective Optimization Method

Selection of Cancer Biomarkers from Microarray Gene Expressi...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Jiang, Hanjing Lin, Jianqing Zhu, Huachao Huang, Yabing Huazhong University of Science and Technology Key Lab. of Image Information Processing and Intelligent Control of Education Ministry of China Institute of Artificial Intelligence School of Artificial Intelligence and Automation Wuhan430074 China Wuhan University School of Computer Science Wuhan430064 China Renmin Hospital of Wuhan University Department of Pathology Wuhan430060 China

ISBN: (纸本)9798350337488

Cancer-associated biomarker genes play an indispensable role in the intricate tapestry of cancer development and manifestation. The expression of biomarkers in different types of tumor cells has beneficial implications for shedding light on the development of various cancers, guiding clinical diagnosis, and treatment. Microarray technology enables the expression levels of thousands of genes in samples to be sequenced simultaneously. However, sparse and high-dimensional microarray data present a formidable challenge in identifying biomarker genes. This study presents EREF-NSGA2, a novel method for cancer biomarker selection from microarray data, employing a hybrid gene selection approach. Firstly, the combination of the wrapper and embedded gene selection methods is proposed to filter the microarray data, which efficiently decreases the search space of the algorithm. After that, the improved NSGA-II algorithm is used to search the genes subset obtained from the previous step to reach the optimal subset of cancer biomarker genes. The proposed EREF-NSGA2 is compared with other reported methods on six cancer benchmark gene expression datasets. A detailed biological analysis is performed to analyze the relationship between the selected genes and the cancer data sets they belong to. To summarize, EREF-NSGA2 proves its effectiveness in selecting a feature subset comprising the fewest genes while maintaining the highest classification accuracy. © 2023 IEEE.

关键词： Bi-objective optimization Cancer biomarker Gene selection NSGA-II

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A Multi-homed VPN Architecture Based on Extended SOCKS+TLS Protocols

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Journal of Shanghai Jiaotong university(science) 2005年第3期10卷 250-255页

作者：张宝良胡汉平陈翔 State Education Ministry Key Lab. of Image Information & Intelligent Control In st. of Pattern Recognition & Artificial Intelligence Huazhong Univ. of Science & Technology Wuhan 430074 China

A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmission connections can switch smoothly among the multiple proxies by maint aining a coherent connection *** mechanism is transparent to application programs and can support th e building of *** the cooperation of some other security components,the mechanism guarantees the reso urce availab.lity and reliability of the end system against some attacks to the specific ports or hosts.

关键词： multi-homed SOCKSv5 security connection context virtual private network （VPN）

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Beta Wave of Sleep Electroencephalogram Analysis Based on Multiscale Sign Series Entropy

Beta Wave of Sleep Electroencephalogram Analysis Based on Mu...

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2015 International Conference on Artificial Intelligence and Industrial Engineering(AIIE 2015)

作者： Jianhui Jiang Shitong Wang Fengzhen Hou Jun Wang Jin Li Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm School of Science China Pharmaceutical University College of Physics and Information Technology Shaanxi Normal University

ISBN: (纸本)9781510806450

Sleep Electroencephalogram(Sleep EEG) detection and treatment can provide the basis for clinical diagnosis and treatment. According to the non-stationary random character of EEG itself, the paper proposed multiscale sign series entropy(MSSE) method and applied it to the state of sleep EEG analysis. Numerical results showed that, MSSE method can effectively differentiate awake period β wave and sleep stage β wave even if under the influence of the noise. The results show that the algorithm can aid in clinical diagnosis of sleep EEG.

关键词： sleep electroencephalogram multiscale sign series entropy clinical diagnosis

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Feedback alfa-rooting algorithm for medical image enhancement 17

Feedback alfa-rooting algorithm for medical image enhancemen...

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17th image Processing: Algorithms and Systems Conference, IPAS 2019

作者： Voronin, V. Zelensky, A. Agaian, S. Don State Technical University Lab. «Mathematical Methods of Image Processing and Computer Vision Intelligent Systems» Gagarina 1 Rostov on Don Russia Moscow State University of Technology "STANKIN" Moscow Russia CUNY/ College of Staten Island Dept. of Computer Science New York United States

This paper presents a new combined local and global transform domain-based feedback image enhancement algorithm for medical diagnosis, treatment, and clinical research. The basic idea in using local alfa-rooting method is to apply it to different disjoint blocks with different sizes. The block size and alfa-rooting parameters driven through optimization using the Agaian's cost function (image enhancement non-reference quality measure). The presented new approach allows enhancing MRI and CT images with uneven lighting and brightness gradient by preserving the local image features/details. Extensive computer simulations (CS) on real medical images are offered to gage the presented method. CS shows that our method improves the contrast and enhances the details of the medical images effectively compared with the current state-of-art methods. © 2019, Society for Imaging science and technology.

关键词： Clinical research

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An active contour model for medical image segmentation using a quaternion framework 18

An active contour model for medical image segmentation using...

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18th image Processing: Algorithms and Systems Conference, IPAS 2020

作者： Voronin, V. Zhdanova, M. Semenishchev, E. Zelensky, A. Agaian, S. Moscow State University of Technology "STANKIN" Moscow Russia Don State Technical University Lab. «Mathematical methods of image processing and computer vision Intelligent Systems» Gagarina 1 Rostov on Don Russia CUNY/ College of Staten Island Dept. of Computer Science New York United States

This paper presents a new method for segmenting medical images is based on Hamiltonian quaternions and the associative algebra, method of the active contour model and LPA-ICI (local polynomial approximation - the intersection of confidence intervals) anisotropic gradient. Since for segmentation tasks, the image is usually converted to grayscale, this leads to the loss of important information about color, saturation, and other important information associated color. To solve this problem, we use the quaternion framework to represent a color image to consider all three channels simultaneously when segmenting the RGB image. As a method of noise reduction, adaptive filtering based on local polynomial estimates using the ICI rule is used. The presented new approach allows obtaining clearer and more detailed boundaries of objects of interest. The experiments performed on real medical images (Z-line detection) show that our segmentation method of more efficient compared with the current state-of-art methods. © 2020, Society for Imaging science and technology

关键词： Adaptive filtering

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Modified color co-occurrence matrix for image retrieval

Modified color co-occurrence matrix for image retrieval

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First International Conference on Natural Computation, ICNC 2005

作者： Chang, Min Hyuk Pyun, Jae Young Ahmad, Muhammad Bilal Chun, Jong Hoon Park, Jong An Dept. of Information and Communications Engineering Chosun University Gwangju Korea Republic of Signal and Image Processing Lab. Dept. of Mechatronics Gwangju Institute of Science and Technology Gwangju Korea Republic of Dept. of Computer Information and Communication Eng. Jeonnam Provincial Collage Jeonnam Korea Republic of

Color correlogram for content-based image retrieval (CBIR) characterizes not only the color distribution of pixels, but also the spatial correlation of pairs of colors. Color not only reflects the material of surface, but also varies considerably with the change of illumination, the orientation of the surface, and the viewing geometry of the camera. The invariance to these environmental factors is not considered in most of the color features in color based CBIR including the color correlogram. However, pixels changed their color with almost same proportions with change of environmental factors. This fact is taken into consideration, and new algorithm is proposed. The color cooccurrence matrix for different spatial distances is defined based on the maximum/minimum of color component between the three components (R,G,B) of a pixel. The proposed algorithm has less number of features, and the change of illumination, etc. is also taken into account. © Springer-Verlag Berlin Heidelberg 2005.

关键词： image retrieval

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The quaternion-based anisotropic gradient for the color images 17

The quaternion-based anisotropic gradient for the color imag...

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17th image Processing: Algorithms and Systems Conference, IPAS 2019

作者： Voronin, V. Zelensky, A. Agaian, S. Don State Technical University Lab. «Mathematical Methods of Image Processing and Computer Vision Intelligent Systems» Gagarina 1 Rostov on Don Russia Moscow State University of Technology"STANKIN" Moscow Russia CUNY College of Staten Island Dept. of Computer Science New York United States

image gradient, as a preprocessing step is an essential tool in image processing in many research areas such as edge detection, segmentation, smoothing, inpainting, etc. In the present paper, we develop a new gradient by integrated the quaternion framework with LPA-ICI (local polynomial approximation - the intersection of confidence intervals) based on anisotropic gradient concepts for the color image processing applications. Computer simulations on the Berkeley Segmentation Dataset show that the new quaternion anisotropic gradient exhibits fewer color artifacts compared to state-of-the-art techniques including well-knowledge gradient operators. © 2019, Society for Imaging science and technology.

关键词： Polynomial approximation

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Automatic needle segmentation using 3D Gray-level Hough Transform in 3D ultrasound images

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Journal of Computational Information Systems 2008年第5期4卷 2021-2026页

作者： Qiu, Wu Ding, Mingyue Yuchi, Ming Image Processing and Intelligence Control Key Lab. of Education Ministry of China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Department of Biomedical Engineering School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

This paper describes a novel 3D needle segmentation algorithm for 3DUS data. The algorithm includes the 3D Gray-level Hough Transform (3DGHT), which is based on the representation (ψ, θ, ρ, α) of straight lines in 3D space and Local Dimensionality Estimator (GST). Different from the traditional Hough transformation the process of binarization is not needed, because the proposed algorithm adopts the original gray level image directly. We tested it with the synthetic data and water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1° and position deviation less than 1 mm. © 2008 Binary Information Press.

关键词： Hough transforms

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Multi-homed VPN architecture based on extended SOCKS+TLS protocols

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Journal of Shanghai Jiaotong University (science) 2005年第3期10 E卷 250-255页

作者： Zhang, Bao-Liang Hu, Han-Ping Chen, Xiang State Education Ministry Key Lab. of Image Information and Intelligent Control Inst. of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Science and Technology Wuhan 430074 China

A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system, in which the security-demanded transmission connections can switch smoothly among the multiple proxies by maintaining a coherent connection context. The mechanism is transparent to application programs and can support the building of VPN. With the cooperation of some other security components, the mechanism guarantees the resource availab.lity and reliability of the end system against some attacks to the specific ports or hosts.

关键词： Virtual reality

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