检索结果-内蒙古大学图书馆

automatic image segmentation based on label propagation

IET image PROCESSING 2021年第11期15卷 2532-2547页

作者： Belizario, Ivar Vargas Linares, Oscar Cuadros Santo Batista Neto, Joao do Espirito Univ Sao Paulo Inst Math & Comp Sci ICMC Sao Carlos Brazil

This article introduces an automatic approach for the segmentation of coloured natural scene images based on graphs and the propagation of labels originally designed for communities detection in complex networks. images are initially pre-segmented with super-pixels, followed by feature extraction using colour information of each super-pixels. The resulting graph consists of vertices which represent super-pixels, whereas the edge weights are a measure of similarity between super-pixels. The resulting segmentation corresponds to the propagation of labels among the vertices. In this article, three strategies for propagating labels have been formulated: (i) iterative propagation (ILP), (ii) recursive propagation (RLP) and (iii) a weighted recursive propagation (WRLP). The experiments have shown that the proposed methods, when compared to other state-of-the-art methods, produce better results in terms of segmentation quality and processing time.

关键词： iterative methods coloured natural scene images weighted recursive propagation vertices ILP Computer vision and image processing techniques iterative propagation label propagation Optical, image and video signal processing super pixels image segmentation natural scenes resulting segmentation corresponds graph theory feature extraction Interpolation and function approximation (numerical analysis) graphs colour information segmentation quality automatic image segmentation RLP Combinatorial mathematics

来源：评论

学校读者我要写书评

暂无评论

Fully automatic image segmentation based on FCN and graph cuts

引用

MULTIMEDIA SYSTEMS 2022年第5期28卷 1753-1765页

作者： Wang, Zhaobin Gao, Xiong Wu, Runliang Kang, Jianfang Zhang, Yaonan Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Chinese Acad Sci Natl Cryosphere Desert Data Ctr Lanzhou 730000 Peoples R China Chinese Acad Sci Northwest Inst Ecoenvironm & Resources Lanzhou 730000 Peoples R China

Due to the posteriori knowledge provided by the Human-Computer Interaction algorithms, interactive segmentation based on Graph Cuts can successfully extract the foreground in an image, which will, however, limit the scope of their application. Inspired by recent years of research on computer vision with fully convolutional neural networks, a fully automated image segmentation method based on FCN and Graph Cuts has been proposed. First, FCN is employed to obtain an original mask for the input image, but its boundary is poor. Second, we generate seed regions heuristically using color histograms and mathematical morphological operations on the original mask. Finally, iterative segmentation is performed using generative seeds and superpixel-level Graph Cuts. Experimental results show that our method has higher segmentation accuracy compared to other representative methods including interactive and automatic segmentation.

关键词： automatic image segmentation Graph cuts FCN Color histogram Superpixel

来源：评论

学校读者我要写书评

暂无评论

Ship Target Imaging in Airborne SAR System Based on automatic image segmentation and ISAR Technique

引用

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2021年 14卷 1985-2000页

作者： Cao, Rui Wang, Yong Zhao, Bin Lu, Xiaofei Harbin Inst Technol Res Inst Elect Engn Technol Harbin 150001 Peoples R China Jiuquan Satellite Launch Ctr Jiuquan 732750 Peoples R China

The airborne synthetic aperture radar (SAR) image of ship target will be blurred for the complex motion of the target, which will influence the performance of feature extraction and target classification. In this article, a refocusing method of ship target in airborne SAR image though the inverse synthetic aperture radar (ISAR) technique is presented. The novel contributions of this article can be summarized as follows: 1) the residual phase of processed signal is analyzed in detail to illustrate the necessity of adopting ISAR technique;2) a valid, labor-saving, and automatic image segmentation approach via clustering algorithm is put forward for automatic data extraction and inverse mapping. The clustering algorithm we choose is the agglomerative hierarchical cluster algorithm, which does not require the number of categories in advance;3) the refocused individual ISAR image of individual ship target is yielded though the range-instantaneous Doppler algorithm. Finally, the simulated and real measured data are processed, and imaging results verify the effectiveness of the novel algorithm presented in this article.

关键词： automatic image segmentation clustering algorithm hierarchical cluster algorithm (HCA) inverse synthetic aperture radar (ISAR) refocusing ship target synthetic aperture radar (SAR)

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Machine Learning for automatic image segmentation of Impact Damage in CFRP Composites

引用

APPLIED COMPOSITE MATERIALS 2024年第6期31卷 1849-1867页

作者： Zhupanska, Olesya Krokhmal, Pavlo Univ Arizona Dept Aerosp & Mech Engn Tucson AZ 85721 USA Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA

In this work, a novel unsupervised machine learning (ML) method for automatic image segmentation of low velocity impact damage in carbon fiber reinforced polymer (CFRP) composites has been developed. The method relies on the use of non-parametric statistical models in conjunction with the so-called intensity-based segmentation, enabling one to determine the thresholds of image histograms and isolate the damage. Statistical distance metrics, including the Kullback-Leibler divergence, the Helling distance, and the Renyi divergence are used to formulate and solve optimization problems for finding the thresholds. The developed method enabled rigorous and rapid automatic image segmentation of the grayscale images from the micro computed tomography (micro-CT) scans of the impacted CFRP composites. Sensitivity of the segmentation results with respect to the thresholds obtained using different statistical distances has been investigated. Based on the analysis of the segmentation results, it is concluded that the Kullback-Leibler divergence is the most appropriate statistical measure and should be used for automatic image segmentation of impact damage in CFRP composites.

关键词： Carbon fiber polymer matrix composite Low velocity impact Computed tomography automatic image segmentation Unsupervised machine learning

来源：评论

学校读者我要写书评

暂无评论

Performance of automatic image segmentation algorithms for calculating total lesion glycolysis for early response monitoring in non-small cell lung cancer patients during concomitant chemoradiotherapy

引用

RADIOTHERAPY AND ONCOLOGY 2016年第3期119卷 473-479页

作者： Grootjans, Willem Usmanij, Edwin A. Oyen, Wim J. G. van der Heijden, Erik H. F. M. Visser, Eric P. Visvikis, Dimitris Hatt, Mathieu Bussink, Johan de Geus-Oei, Lioe-Fee Radboud Univ Nijmegen Med Ctr Dept Radiol & Nucl Med Nijmegen Netherlands Leiden Univ Med Ctr Dept Radiol POB 9600 NL-2300 RC Leiden Netherlands Inst Canc Res London England Royal Marsden NHS Fdn Trust London England Radboud Univ Nijmegen Med Ctr Dept Pulm Med Nijmegen Netherlands INSERM UMR 1101 Lab Traitement Informat Med LaTIM Brest France Radboud Univ Nijmegen Med Ctr Dept Radiat Oncol Nijmegen Netherlands Univ Twente MIRA Inst Biomed Photon Imaging Grp Enschede Netherlands

Background and purpose: This study evaluated the use of total lesion glycolysis (TLG) determined by different automatic segmentation algorithms, for early response monitoring in non-small cell lung cancer (NSCLC) patients during concomitant chemoradiotherapy. Materials and methods: Twenty-seven patients with locally advanced NSCLC treated with concomitant chemoradiotherapy underwent F-18-fluorodeoxyglucose (FDG) PET/CT imaging before and in the second week of treatment. segmentation of the primary tumours and lymph nodes was performed using fixed threshold segmentation at (i) 40% SUVmax (T40), (ii) 50% SUVmax (T50), (iii) relative-threshold-level (RTL), (iv) signal-to-background ratio (SBR), and (v) fuzzy locally adaptive Bayesian (FLAB) segmentation. Association of primary tumour TLG (TLGT), lymph node TLG (TLGLN), summed TLG (TLG(S) = TLG(T) + TLG(LN)), and relative TLG decrease (Delta TLG) with overall -survival (OS) and progression-free survival (PFS) was determined using univariate Cox regression models. Results: Pretreatment TLG(T) was predictive for PFS and OS, irrespective of the segmentation method used. Inclusion of TLG(LN) improved disease and early response assessment, with pretreatment TLG(S) more strongly associated with PFS and OS than TLG(T) for all segmentation algorithms. This was also the case for Delta TLG(S), which was significantly associated with PFS and OS, with the exception of RTL and T40. Conclusions: Delta TLG(S) was significantly associated with PFS and OS, except for RTL and T40. Inclusion of TLG(LN) improves early treatment response monitoring during concomitant chemoradiotherapy with FDG-PET. (C) 2016 Elsevier Ireland Ltd. All rights reserved.

关键词： Early response monitoring Non-small cell lung cancer Concomitant chemoradiochemotherapy F-18-FDG PET/CT Total lesion glycolysis automatic image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Fully automatic image segmentation Using an Extended Fuzzy Set

A Fully Automatic Image Segmentation Using an Extended Fuzzy...

引用

International Workshop on Computer Science for Environmental Engineering and EcoInformatics (CSEEE)

作者： Zhang, Ling Zhang, Ming Shandong Univ Sch Math & Syst Sci Jinan 250100 Shandong Peoples R China Utah State Univ Dept Comp Sci Logan UT 84322 USA

ISBN: (纸本)9783642226915

segmentation is a key step in image processing. Most existing segmentation algorithm doesn't work on blurry images. In medical CAD system, it is difficult to do segmentation fully automatically due to the property of images. In this paper, we employ a novel extended fuzzy watershed method for image segmentation and develop a fully automatic algorithm for breast ultrasound (BUS) image segmentation. A (U) domain is defined and employed to evaluate the uncertainty. The experiments show that our approach is fully automatic. It can get good results on blurry ultrasound images.

关键词： automatic image segmentation Fuzzy Set Uncertainty Ultrasound image

来源：评论

学校读者我要写书评

暂无评论

automatic MEDICAL image segmentation BASED ON EPGV-SNAKE

AUTOMATIC MEDICAL IMAGE SEGMENTATION BASED ON EPGV-SNAKE

引用

6th International Multi-Conference on Systems, Signals and Devices

作者： Bakir, Houda Charfi, Maher Ecole Super Sci & Tech Tunis BP 56 Tunis 1008 Tunisia Fac Med Unit Rech Biophys Tunis Tunisia

ISBN: (纸本)9781424443451

This communication presents a novel approach to contour segmentation of Computed Tomography (CT) images. image segmentation is achieved by means of the snake algorithm and the dynamic programming (DP) optimization technique. Based upon the edge preserving gradient vector flow (EPGVF) field, a new strategy for contour points initialization and splitting is presented. Contour initialization is carried out from EPGVF magnitude thresholding. In the multi-object image segmentation, the delineation of all the image objects is done through the splitting of the contour at the divergent points in the image. The proposed technique can attain a good solution without the need of an operator intervention. Some experiences on synthetic and CT medical images show that the proposed algorithm gives good results.

关键词： automatic image segmentation EPGVF-Snake contour initialization contour splitting

来源：评论

学校读者我要写书评

暂无评论

automatic segmentation and classification of human brain image based on a fuzzy brain atlas

Automatic segmentation and classification of human brain ima...

引用

International Symposium on Multispectral image Processing and Pattern Recognition

作者： Tan, O Jia, CG Duan, HL Lu, WX Zhejiang Univ Inst Biomed Engn Hangzhou 310027 Peoples R China

ISBN: (纸本)0819430064

It is difficult to automatically segment and classify tomograph images of actual patient's brain. Therefore, many interactive operations are performed. It is very time consuming and its precision is much depended on the user. In this paper, we combine a brain atlas and 3D fuzzy image segmentation into the image matching. It can not only find our the precise boundary of anatomic structure but also save time of the interactive operation. At first, the anatomic information of atlas is mapped into tomograph images of actual brain with a two step image matching method. Then, based on the mapping result, a 3D fuzzy structure mask is calculated. With the fuzzy information of anatomic structure, a new method of fuzzy clustering based on genetic algorithm is used to segment and classify the real brain image. There is only a minimum requirement of interaction in the whole process, including removing the skull and selecting some intrinsic point pairs.

关键词： automatic image segmentation image matching brain atlas shape factor genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

automatic Tuning of the Pulse-Coupled Neural Network Using Differential Evolution for image segmentation 8th

Automatic Tuning of the Pulse-Coupled Neural Network Using D...

引用

8th Mexican Conference on Pattern Recognition (MCPR)

作者： Hernandez, Juanita Gomez, Wilfrido Natl Polytech Inst Ctr Res & Adv Studies Informat Technol Lab Ciudad Victoria Tamaulipas Mexico

ISBN: (纸本)9783319393933;9783319393926

The pulse-coupled neural network (PCNN) is based on the cortical model proposed by Eckhorn and is widely used in tasks such as image segmentation. The PCNN performance is particularly limited by adjusting its input parameters, where computational intelligence techniques have been used to solve the problem of PCNN tuning. However, most of these techniques use the entropy measure as a cost function, regardless of the relationship of inter-/intra-group dispersion of the pixels related to the objects of interest and their background. Therefore, in this paper, we propose using the differential evolution algorithm along with a cluster validity index as a cost function to quantify the segmentation quality in order to guide the search to the best PCNN parameters to get a proper segmentation of the input image.

关键词： automatic image segmentation Pulse-coupled neural network Differential evolution Cluster validity index

来源：评论

学校读者我要写书评

暂无评论

An elliptical level set method for automatic TRUS prostate image segmentation

An elliptical level set method for automatic TRUS prostate i...

引用

6th IEEE International Symposium on Signal Processing and Information Technology

作者： Kachouie, Nezamoddin N. Fieguth, Paul Rahnamayan, Shahryar Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780780397538

One of the most important tasks in prostate cancer diagnosis and treatment is segmentation of Transrectal Ultrasound (TRUS) prostate images. Due to the large volumes of TRUS prostate images, automatic segmentation systems are mandatory. Weak prostate boundaries, speckle noise and the short range of gray levels make the task more challenging and difficult. Deformable models have been considered as an effective approach for semi-automatic prostate segmentation. However the main problem toward a fully automatic segmentation system using deformable models is initialization of seed or control points. In this paper an automatic level set prostate segmentation is presented A classification method is employed to locate the approximate location of the prostate which is used to initiate the proposed elliptical level set contour The deformations of the level set are guided by a velocity function which is derived using the TRUS prostate image histogram.

关键词： automatic image segmentation deformable models level sets ultrasound imaging TRUS prostate image classification image morphology thresholding speckle noise

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：