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Attenuation correction with region growing method used in the positron emission mammography imaging system

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Chinese Physics C 2015年第10期39卷 131-138页

作者：顾笑悦李琳尹鹏飞负明凯柴培黄先超孙校丽魏龙 Key Laboratory of Nuclear Radiation and Nuclear Energy Technology Institute of High Energy PhysicsChinese Academy of Sciences Beijing Engineering Research Center of Radiographic Techniques and Equipment

The Positron Emission Mammography imaging system （PEMi） provides a novel nuclear diagnosis method dedicated for breast imaging. With a better resolution than whole body PET, PEMi can detect millimeter-sized breast tumors. To address the requirement of semi-quantitative analysis with a radiotracer concentration map of the breast, a new attenuation correction method based on a three-dimensional seeded region growing image segmentation （3DSRG-AC） method has been developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuity property of the segmentation result makes this new method free of activity variation of breast tissues. The threshold value chosen is the key process for the segmentation method. The first valley ill the grey level histogram of the reconstruction image is set as the lower threshold, which works well in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probability of detecting small and early breast tumors.

关键词： breast PET attenuation correction region growing image segmentation

A fast and efficient mesh segmentation method based on improved region growing

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Applied Mathematics(A Journal of Chinese Universities) 2014年第4期29卷 468-480页

作者： YANG Fei ZHOU Fan WANG Ruo-mei LIU Li LUO Xiao-nan School of Information Science and Technology Sun Yat-sen University National Engineering Research Center of Digital Life

Mesh segmentation is one of the important issues in digital geometry processing. region growing method has been proven to be a efficient method for 3D mesh segmentation. However, in mesh segmentation, feature line extraction algorithm is computationally costly, and the over-segmentation problem still exists during region merging processing. In order to tackle these problems, a fast and efficient mesh segmentation method based on improved region growing is proposed in this paper. Firstly, the dihedral angle of each non-boundary edge is defined and computed simply, then the sharp edges are detected and feature lines are extracted. After region growing process is finished, an improved region merging method will be performed in two steps by considering some geometric criteria. The experiment results show the feature line extraction algorithm can obtain the same geometric information fast with less computational costs and the improved region merging method can solve over-segmentation well.

关键词： mesh segmentation feature line region growing dihedral angle.

Unstructured Road Detection Based on region growing

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Unstructured Road Detection Based on Region Growing

第30届中国控制与决策会议

作者： Li Xiaolin Ji Yufeng Gao Yan Feng Xiaoxue Li Weixing School of Automation Beijing Institute of Technology

Image based road detection is a vital and challenging task in many real-world applications such as autonomous driving,road departure *** this paper,we study the problem of unstructured road detection from a color *** algorithm we propose decomposes the road detection into three steps:the estimation of the horizon line by similarity measurement,followed by the road area prediction based upon the estimated horizon line,and region growing to segment the image into road and non-road *** road area prediction provides good road *** region growing is effective to detect the road region utilizing the feature extracted from the road *** results demonstrate that the proposed algorithm is accurate and efficient.

关键词： Unstructured road detection Horizon line estimation Road area prediction region growing

Automatic 3D lung nodule detection based on shape filter and region growing

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Automatic 3D lung nodule detection based on shape filter and...

第三十九届中国控制会议

作者： Shu-an Liu Xiaoxue Xu Xiaonan Yang Qiongyang Liu Jun Gong School of Information Science and Engineering Northeastern University

Lungs cancer is a fatal disease. However, its early detection increases the chances of survival among patients. An automated nodule detection system provides the second opinion to radiologists in early diagnosis. In the detection of pulmonary nodules, the complex vessel structure similar to lung nodules in grayscale is an important factor that interferes with the accurate detection of pulmonary nodules. In this paper, we proposed a novel automatic 3 D lung nodule detection approach in computed tomography studies. Firstly, the lung region is extracted on the basis of the region growing and morphological smoothing. In the next phase, Frangi multiscale enhancement filter based on the eigenvalues of the Hessian matrix is used to enhance the vessel structures with different size and shapes, and then the fuzzy C-means clustering method（FCM） was used to segment and remove the blood vessels. We apply spherical-like filter based on 3 D shape index to detect lung nodule on 3 D lung parenchyma data. In the last step, Support Vector Machine（SVM） is used for *** results show that this method can effectively reduce the impact of blood vessels on the detection of pulmonary nodules and improve the accuracy of detection of pulmonary nodules.

关键词： lung nodule detection region growing shape filter CT images

Autonomous exploration of RRT robot based on seeded region growing

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Autonomous exploration of RRT robot based on seeded region g...

第三十九届中国控制会议

作者： Zeyu Tian Chen Guo Yi Liu Tianxiao Cui College of Marine Electrical Engineering Dalian Maritime University

When the indoor environment is unknown,how to make robots carry out effective autonomous exploration and construct related maps is one of the key issues in the field of mobile *** to the complexity of the real-world environment,how to build high-quality maps during the same exploration process is an important evaluation index for the autonomous exploration of mobile ***,a rapid-exploration random tree（RRT）-based robot autonomous exploration method based on seed region growth is *** method uses two-dimensional laser data,which mainly includes four steps:extraction of seed line segments,region growth,overlapping region processing,and impurity point *** the grown laser data as a new sensor data input,a two-sided RRT boundary exploration is *** RRT exploration is used to detect the boundary points around the mobile robot;global RRT boundary exploration is used to detect the boundary points at the far end of the robot and the small corners on the *** two methods are merged to speed up the search for boundary *** the optimal boundary point is obtained,the robot is continuously moved to the best advantage through closed-loop *** effectiveness of the proposed method is verified by simulation experiments and actual scenarios in a robot operating system（ROS）.

关键词： region growing Rapidly-Exploring Random Tree(RRT) Boundary Exploration Mapping

Power Line Detection Based on region growing and Ridge-Based Line Detector

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Power Line Detection Based on Region Growing and Ridge-Based...

2013年中国智能自动化学术会议

作者： Xiwen Yao Lei Guo Tianyun Zhao School of Automation Northwestern Polytechnical University

Automatic power line detection is one of the most important and challenging tasks for helicopter’s low flight to avoid the power-line-strike accident. In this paper,we propose a novel method to detect power lines in the infrared ***,region growing is used to get the line support *** a ridgebased line detector is applied to extract the accurate power lines points in the support regions followed by a linking step combined with chain codes analysis to refine the power *** experimental results against two state-of-the-art line detection algorithms demonstrate the performance of the proposed algorithm.

关键词： Power line detection region growing Ridge-based line detector

A hybrid image segmentation algorithm based on edge detection, thresholding and region growing

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A hybrid image segmentation algorithm based on edge detectio...

2007亚洲光电子会议电子成像与多媒体技术分会场

This hybrid segmentation algorithm presented is a combination of three traditional methods. It has some advantages that traditional methods don’t have: first, the edge detected is continuous;second, segmentation result is accurate;third, overgrowing doesn’t exist. The hybrid algorithm has been implemented on some images. Through the segmentation result, it is proved to be effective.

关键词： image segmentation edge detection thresholding region growing

Line laser point cloud segmentation based on the combination of RANSAC and region growing 112

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Line laser point cloud segmentation based on the combination...

第三十九届中国控制会议

作者： Henan Yuan Wei Sun Tianyuan Xiang College of Electrical and Information Engineering Hunan University Aerospace Information Research Institute Chinese Academy of Sciences

RANdom SAmpling Consensus（RANSAC） and region growing algorithms are widely used in image processing and point cloud segmentation, but the RANSAC algorithm used for point cloud segmentation will cause insufficient segmentation. The region growing algorithm can divide point cloud data into points based on the curvature and normal characteristics of the point cloud. Multiple clusters are easy to be over-segmented. To solve this problem, this paper proposes to use the RANSAC algorithm to perform coarse segmentation to segment the point cloud data into a foreground point cloud with more geometric features and a background point cloud that is only a plane. Then use the region growing algorithm. The foreground point cloud is finely segmented. Besides, the curvature characteristics of the region growing process are used to optimize the plane extraction of the RANSAC algorithm. The experimental results show that this method can reduce over-segmentation to a certain extent and significantly improve the speed of the algorithm.

关键词： point cloud segmentation RANSAC region growing line laser

Crack identification method of highway tunnel based on image processing

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Journal of Traffic and Transportation Engineering(English Edition) 2023年第3期10卷 469-484页

作者： Guansheng Yin Jianguo Gao Jianmin Gao Chang Li Mingzhu Jin Minghui Shi Hongliang Tuo Pengfei Wei School of Sciences Chang'an UniversityXi'an 710064China School of Transportation Science and Engineering Civil Aviation University of ChinaTianjin 300300China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China

In this paper,the images of tunnel surface are obtained by tunnel lining rapid inspection system,and tunnel crack forest dataset(TCFD)is *** disaster characteristics of tunnel cracks are analyzed and *** of tunnel crack segmentation(TCS)method are developed for the detection and recognition of cracks on tunnel *** to the image features of the tunnel lining and the optical principal of detection equipment,effective image pre-processing steps are carried out before crack *** tunnel image of TCFD is divided into appropriate number of blocks to magnify the local features of tunnel *** threshold segmentation method is used to traverse the blocks successively,and the first target block with crack is *** seed in the target block were obtained by adaptive localization method and mapped to the whole *** growing is performed through crack seed until complete tunnel crack is *** results show that the precision,recall rate and F-measure of tunnel cracks under the TCS method can reach 92.58%,93.07%and 92.82%without strong *** to the binary images processed by TCS method,the projection images of different types of tunnel cracks and their respective laws are ***,the TCS method is implemented and deployed as a GUI software application.

关键词： Tunnel engineering Crack identification Image binarization Tunnel crack region growing Contrast limited adaptive histogram equalization