检索结果-内蒙古大学图书馆

作者： Yuehuan Wang Guirong Weng School of Mechanical and Electrical Engineering Soochow University

As is known,agriculture is very important in China,but the problem about pests has hampered the further development of Chinese *** image-processing technology and mathematical morphology are referred to as the main research methods,and tiny pets like aphids among field are referred to as the research *** processing technology such as edgeenhancing diffusion filtering,mathematical morphology and watershed segmentation algorithm is used to monitor pest population density,which greatly raises efficiency of pest data *** the segmentation of the image of the pests,the number of the insect individuals can be obtained from the background by using image processing *** image processing technology provides a possibility to solve this problem and becomes a very important direction to monitor regional pest population density.

关键词： Digital Image-processing Monitoring Population Mathematical Morphology watershed algorithm Edge-enhancing filtering

来源：评论

学校读者我要写书评

暂无评论

Flooding-based watershed algorithm and its prototype hardware architecture

引用

IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING 2004年第3期151卷 224-234页

作者： Rambabu, C Chakrabarti, I Mahanta, A Indian Inst Technol Dept Elect & Commun Engn Gauhati 781039 India

watershed transformation is a powerful image segmentation technique. The potential of its real-time application can be realised by a dedicated hardware architecture. However, little work has been reported so far on hardware realisation of watershed transformation. The authors propose an improved watershed algorithm derived from Meyer's simulated flooding-based algorithm by ordered queues and a prototype FPGA-based architecture for its effective implementation. The improvement in computational complexity results from use of a single queue and conditional neighbourhood comparisons while processing the 3 X 3 neighbouring pixels. Besides analysing the computational complexity of the principal steps of the proposed algorithm, the authors present simulation results of running the proposed algorithm and the conventional algorithm on different images for comparison. The proposed architecture has been modelled in VHDL and synthesised for Virtex FPGA. The implementation results show acceptable performance of the proposed architecture.

关键词： .neighbourhood hardware architecture grey scale watershed algorithm flooding watershed lines watershed transformation

来源：评论

学校读者我要写书评

暂无评论

Segmentation of tumors in magnetic resonance brain images using an interactive multiscale watershed algorithm

引用

ACADEMIC RADIOLOGY 2004年第10期11卷 1125-1138页

作者： Letteboer, MMJ Olsen, OF Dam, EB Willems, PWA Viergever, MA Niessen, WJ Univ Utrecht Ctr Med Image Sci Inst NL-3584 CX Utrecht Netherlands Univ Utrecht Ctr Med Dept Neurosurg NL-3584 CX Utrecht Netherlands IT Univ Copenhagen Dept Innovat Copenhagen Denmark

Rationale and Objective. This article presents the evaluation of an interactive multiscale watershed segmentation algorithm for segmenting tumors in magnetic resonance brain images of patients scheduled for neuronavigational procedures. Materials and Methods. The watershed method is compared with manual delineation with respect to accuracy, repeatability, and efficiency. Results. In the 20 patients included in this study, the measured volume of the tumors ranged from 2.7 to 81.9 cm(3). A comparison of the tumor volumes measured with watershed segmentation to the volumes measured with manual delineation shows that the two methods are interchangeable according to the Bland and Altman criterion, and thus equally accurate. The repeatability of the watershed method and the manual method are compared by looking at the similarity of the segmented volumes. The similarity for intraobserver and interobserver variability for watershed segmentation is 96.4% and 95.3%, respectively, compared with 93.5% and 90.0% for manual outlining, from which it may be concluded that the watershed method is more repeatable. Moreover, the watershed algorithm is on average three times faster than manual outlining. Conclusion. The watershed method has an accuracy comparable to that of manual delineation and outperforms manual outlining on the criteria of repeatability and efficiency. (C) AUR, 2004.

关键词： brain magnetic resonance imaging (MRI) brain tumors interactive segmentation multiscale image segmentation watershed algorithm

来源：评论

学校读者我要写书评

暂无评论

Automatic segmentation of the liver in CT images using the watershed algorithm based on morphological filtering

Automatic segmentation of the liver in CT images using the w...

引用

Medical Imaging 2004 Conference

作者： Lim, SJ Jeong, YY Lee, CW Ho, YS Kwangju Inst Sci & Technol Kwangju 500712 South Korea

ISBN: (纸本)0819452831

Liver segmentation is one of the most basic and important parts in computer-aided diagnosis for liver CT. Although various segmentation methods have been proposed for medical imaging. most of them generally do not perform well in segmenting the liver from CT images because of surface features of the liver and difficulty of discrimination from other adjacent organs. In this paper, we propose a new scheme for automatic segmentation of the liver in CT images. The proposed scheme is carried out on region-of-interest (ROI) blocks that include regions of the liver with high probabilities. The ROI approach saves unnecessary computational loss in finding the accurate boundary of the liver. The proposed method utilizes the composition of morphological filters with a priori knowledge, such as the general location or the approximate intensity of the liver to detect the initial boundary of the liver. Then. we make the gradient image with the weight of an initial liver boundary and segment the liver region by using an immersion-based watershed algorithm in the gradient image. Finally, a refining process is carried out to acquire a more accurate liver region.

关键词： morphological operation edge detection watershed algorithm region merging

来源：评论

学校读者我要写书评

暂无评论

Integration of synthetic aperture radar image segmentation method using Markov random field on region adjacency graph

引用

IET RADAR SONAR AND NAVIGATION 2007年第5期1卷 348-353页

作者： Xia, G.-S. He, C. Sun, H. Wuhan Univ Signal Proc Lab Elect Informat Sch Wuhan 430079 Hubei Peoples R China

A novel approach to obtain precise segmentation of synthetic aperture radar (SAR) images using Markov random field model on region adjacency graph (MRF-RAG) is presented. First, to form a RAG, the watershed algorithm is employed to obtain an initially over-segmented image. Then, a novel MRF is defined over the RAG instead of pixels so that the erroneous segmentation caused by speckle in SAR images can be avoided and the number of configurations for the combinatorial optimisation can be reduced. Finally, a modification method based on Gibbs sampler is proposed to correct edge errors, brought by the over-segmented algorithm, in the segmentations obtained by MRF-RAG. The experimental results both on simulated and real SAR images show that the proposed method can reduce the computational complexity greatly as well as increase the segmentation precision.

关键词： error correction combinatorial mathematics synthetic aperture radar image segmentation method radar imaging image segmentation over-segmented algorithm combinatorial optimisation Gibbs sampler Optical, image and video signal processing Combinatorial mathematics Radar equipment, systems and applications watershed algorithm edge error correction SAR images region adjacency graph synthetic aperture radar computational complexity Markov random field model Markov processes

来源：评论

学校读者我要写书评

暂无评论

Segmentation for MRA image: An improved level-set approach

引用

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2007年第4期56卷 1316-1321页

作者： Hao, Jiasheng Shen, Yi Wang, Qiang Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China

Unsupervised segmentation of volumetric data is still a challenging task. Recently, level-set methods have received a great deal of attention, which combine global smoothness with the flexibility of topology changes and offer significant advantages over conventional statistical classification. However, level-set methods suffer from heavy computational burden because of a lot of iterations. We present a fast level-set framework based on the watershed algorithm for the segmentation of complicated structures from a volumetric data set. The driving application is the segmentation of 3-D human cerebrovascular structures from magnetic resonance angiography, which is known to be a very challenging segmentation problem due to the complexity of vessel geometry and intensity patterns. Experimental results show that the proposed method gives fast and accurate excellent segmentation.

关键词： biomedical measurements image segmentation level set magnetic resonance angiography (MRA) watershed algorithm

来源：评论

学校读者我要写书评

暂无评论

A multi-model approach to simultaneous segmentation and classification of heterogeneous populations of cell nuclei in 3D Confocal microscope images

引用

CYTOMETRY PART A 2007年第9期71A卷 724-736页

作者： Lin, Gang Chawla, Monica K. Olson, Kathy Barnes, Carol A. Guzowski, John F. Bjornsson, Christopher Shain, William Roysam, Badrinath Rensselaer Polytech Inst ECSE Dept Troy NY 12180 USA Rensselaer Polytech Inst Ctr Subsurface Sensing & Imaging Syst Troy NY 12180 USA Univ Arizona Inst Brain Tucson AZ USA Univ Calif Irvine Ctr Neurobiol Learning & Memory Irvine CA USA Wadsworth Ctr NYS DOH Cent Nervous Syst Disorders Albany NY USA

Automated segmentation and morphometry of fluorescently labeled cell nuclei in batches of 3D confocal stacks is essential for quantitative studies. Model-based segmentation algorithms are attractive due to their robustness. Previous methods incorporated a single nuclear model. This is a limitation for tissues containing multiple cell types with different nuclear features. Improved segmentation for such tissues requires algorithms that permit multiple models to be used simultaneously. This requires a tight integration of classification and segmentation algorithms. Two or more nuclear models are constructed semiautomatically from user-provided training examples. Starting with an initial over-segmentation produced by a gradient-weighted watershed algorithm, a hierarchical fragment merging tree rooted at each object is built. Linear discriminant analysis is used to classify each candidate using multiple object models. On the basis of the selected class, a Bayesian score is computed. Fragment merging decisions are made by comparing the score with that of other candidates, and the scores of constituent fragments of each candidate. The overall segmentation accuracy was 93.7% and classification accuracy was 93.5%, respectively, on a diverse collection of images drawn from five different regions of the rat brain. The multi-model method was found to achieve high accuracy on nuclear segmentation and classification by correctly resolving ambiguities in clustered regions containing heterogeneous cell populations. (c) 2007 International society for Analytical Cytology.

关键词： cell nuclei segmentation classification watershed algorithm region merging model-based Bayesian estimator parzen window batch processing 3D confocal microscopy

来源：评论

学校读者我要写书评

暂无评论

watershedCounting3D: A new method for segmenting and counting punctate structures from confocal image data

引用

TRAFFIC 2007年第4期8卷 339-346页

作者： Gniadek, Thomas J. Warren, Graham Yale Univ Sch Med Dept Cell Biol New Haven CT 06520 USA

Current research in cell biology frequently uses light microscopy to study intracellular organelles. To segment and count organelles, most investigators have used a global thresholding method, which relies on homogeneous background intensity values within a cell. Because this is not always the case, we developed watershedCounting3D, a program that uses a modified watershed algorithm to more accurately identify intracellular structures from confocal image data, even in the presence of an inhomogeneous background. We give examples of segmenting and counting endoplasmic reticulum exit sites and the Golgi apparatus.

关键词： confocal ER exit site Golgi segmentation watershed algorithm

来源：评论

学校读者我要写书评

暂无评论

An Approach to Semiautomatic Segmentation of Lung Region from 3D-color Images of Frozen Human Body 10th

引用

World Congress on Medical Physics and Biomedical Engineering

作者： Kido, Hideaki Makinouchi, Akifumi Kyushu Univ Grad Sch Syst Life Sci Higashi Ku Fukuoka 812 Japan Grad Sch Informat Sci & Elect Engn Fukuoka Japan

ISBN: (纸本)9783540368397

Segmentation of internal organs from 3D medical images is increasingly focused on by many medical engineering researchers. This paper proposes a new approach to extract the lung region from the 3D-Color Image of Frozen Human Body (Visible Human Male). One of the effective segmentation methods for the medical images is based on the watershed-algorithm. Generally this method has the following steps. First, we detect the edge of the original image. Next, we apply the watershed-algorithm to the image. watershed-algorithm segments image into too many small regions, so usually, we merge these small regions into some groups. To merge regions, some measures of similarity is used. Finally, we select the target group. But with only these steps, the group which is selected is not good. In our case (we use Euclidean distance on RGB color space for the measure), the group includes some regions outside of the target region. It is because that the voxels of small regions have so similar color that the merging step combines the small regions unnecessarily. For example, the over-merged regions are liver, muscle, heart, bronchi, kidney and some other regions. Our goal is how we cut off these unnecessary regions from the selected group and obtain the target lung region. To avoid over-extraction, we introduce three other steps. They are "Edge-Marking", "Reconstruction (shrinking, selecting, and expanding) based on small regions", and "graph-partitioning algorithm". "Edge-Marking" is the process that separates two small regions by giving strong edge feature to boundary voxels between them. "Reconstruction based on small regions" and "Graph-partitioning" are the processes that separates the regions which are connected with narrow bridge. Adding these three processes for the region, other than liver and kidney regions are separated from the lung region. This paper describes these processes and experimental results.

关键词： medical image segmentation watershed algorithm

来源：评论

学校读者我要写书评

暂无评论

Lesion detection using segmentation and classification of mammograms

Lesion detection using segmentation and classification of ma...

引用

IASTED International Conference on Artificial Intelligence and Applications

作者： Vibha, L. Harshavardhan, G. M. Pranaw, K. Shenoy, P. Deepa Venugopal, K. R. Patnaik, L. M. Bangalore Univ Univ Visvesvaraya Coll Engn Dept CSE Bangalore 560001 Karnataka India Indian Inst Sci Microprocessor Applicat Lab Bangalore 560012 Karnataka India

ISBN: (纸本)9780889866294

The national cancer institute (NCI) estimates that 1 in 8 women in USA (12.6%) develop breast cancer, during their life time. Mammography is a medical imaging technique that combines, low-dose radiation and high-contrast, high-resolution film for examination of the breast and screening for breast cancer. The aim of a screening mammogram is to detect a tumor that cannot be physically detected. This paper proposes a method for detection of tumor using watershed algorithm, and further classifies it as benign or malignant using watershed Decision Classifier (WDC). The technique consists of four phases namely, the pre-processing of image, detecting the presence of tumor, creation of the data base and finally classifying and categorizing them into two groups such as Cancerous or Benign. Experimental results show that this method performs well with the classification accuracy reaching nearly 88.38%.

关键词： digital mammography watershed algorithm segmentation random forest classification

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：