检索结果-内蒙古大学图书馆

3d image segmentation by using statistical deformation models and level sets

INTERNATIONAL JOURNAL OF COMPUTER ASSISTEd RAdIOLOGY ANd SURGERY 2006年第3期1卷 123-135页

作者： Fritscher, Karl d. Schubert, Rainer Univ Hlth Sci Med Informat & Technol Inst Biomed Image Anal A-6060 Hall In Tirol Austria

Purpose Improved segmentation of soft objects was sought using a new method that combines level set segmentation with statistical deformation models, using prior knowledge of the shape of an object as well as information derived from the input image. Methods Statistical deformation models were created using Euclidian distance functions of binary data and a multi-hierarchical registration approach based on mutual information metric and demons deformable registration. This approach is motivated by the fact that models based on signed distance maps, traditionally combined with level set segmentation can result in irregular shapes and do not establish explicit correspondences. By using statistical deformation models as representation of shape and a maximum a posteriori (MAP) estimation model to estimate the MAP shape of the object to be segmented, a robust segmentation algorithm using accurate shape models could be developed. Results The accuracy and correctness of the synthesized models was evaluated on different 3d objects (cardiac MRI and spinal CT vertebral segment) and the segmentation algorithm was validated by performing different segmentation tasks using various image modalities. The results of this evaluation are very promising and show the potential utility of the approach. Conclusion Initial results demonstrate the approach is feasible and may be advantageous over alternative segmentation methods. Extensions of the model, which also incorporate prior knowledge about the spatial distribution of grey values, are currently under development.

关键词： 3d image segmentation Level set deformable models Statistical shape models Non-rigid registration

来源：评论

学校读者我要写书评

暂无评论

3d image segmentation of deformable objects with joint shape-intensity prior models using level sets

引用

MEdICAL image ANALYSIS 2004年第3期8卷 285-294页

作者： Yang, J duncan, JS Yale Univ Dept Elect Engn New Haven CT 06520 USA Yale Univ Dept Diagnost Radiol New Haven CT 06520 USA

We propose a novel method for 3d image segmentation, where a Bayesian formulation, based on joint prior knowledge of the object shape and the image gray levels, along with information derived from the input image, is employed. Our method is motivated by the observation that the shape of an object and the gray level variation in an image have consistent relations that provide configurations and context that aid in segmentation. We define a maximum a posteriori (MAP) estimation model using the joint prior information of the object shape and the image gray levels to realize image segmentation. We introduce a representation for the joint density function of the object and the image gray level values, and define a joint probability distribution over the variations of the object shape and the gray levels contained in a set of training images. By estimating the MAP shape of the object, we formulate the shape-intensity model in terms of level set functions as opposed to landmark points of the object shape. In addition, we evaluate the performance of the level set representation of the object shape by comparing it with the point distribution model (PdM). We found the algorithm to be robust to noise and able to handle multidimensional data, while able to avoid the need for explicit point correspondences during the training phase. Results and validation from various experiments on 2d and 3d medical images are shown. (C) 2004 Elsevier B.V. All rights reserved.

关键词： 3d image segmentation shape-intensity joint prior models level set deformable models

来源：评论

学校读者我要写书评

暂无评论

3d image segmentation IMPLEMENTATION ON FPGA USING THE EM/MPM ALGORITHM

3D IMAGE SEGMENTATION IMPLEMENTATION ON FPGA USING THE EM/MP...

引用

2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Sun, Yan Christopher, Lauren A. Indiana Univ Purdue Univ Dept Elect & Comp Engn Indianapolis IN 46202 USA

ISBN: (纸本)9781424442966

In this paper, 3d image segmentation is implemented on Field Programmable Gate Array (FPGA) hardware. segmentation is performed using the EM/MPM Bayesian algorithm. This algorithm segments 3d images using neighboring pixels in a Markov Random Field (MRF) clique. We have implemented this iterative algorithm in Xilinx FPGA, and have achieved greater than 100 times improvement over standard desktop computing hardware. Key to achieving this speed are: a pipelined, parallel data path structure and a novel memory interface for solving the external memory bandwidth problem.

关键词： 3d image segmentation FPGA EM/MPM

来源：评论

学校读者我要写书评

暂无评论

First results for 3d image segmentation with topological map

First results for 3D image segmentation with topological map

引用

14th International Conference on discrete Geometry for Computer imagery

作者： dupas, Alexandre damiand, Guillaume Univ Poitiers SIC XLIM UMR CNRS 6172 Batiment SP2MI F-86962 Futuroscope France Univ Bordeaux 1 UMR CNRS 5800 LaBRI F-33405 Talence France

ISBN: (纸本)9783540791256

This paper presents the first segmentation operation defined within the 3d topological map framework. Firstly we show how a traditional segmentation algorithm, found in the literature, can be transposed on a 3d image represented by a topological map. We show the consistency of the results despite of the modifications made to the segmentation algorithm and we study the complexity of the operation. Lastly, we present some experimental results made on 3d medical images. These results show the process duration of this method and validate the interest to use 3d topological map in the context of image processing.

关键词： topological model 3d image segmentation intervoxel boundaries combinatorial maps

来源：评论

学校读者我要写书评

暂无评论

An Unbiased and Intervoxel Watershed Algorithm for 3d image segmentation

An Unbiased and Intervoxel Watershed Algorithm for 3D Image ...

引用

9th International Conference on image Analysis and Recognition (ICIAR)

作者： Baldacci, Fabien Univ Lyon 1 CREATIS INSA Lyon F-69622 Villeurbanne France

ISBN: (纸本)9783642312953

In this article is presented a new 3d segmentation method based on a watershed transform. The 2d watershed transform is a method known to provide an oversegmentation of the image but with a good boundaries localisation. The extension of the classical watershed to the 3d case does not lead to the same quality because of local configurations when dealing with multiple materials intersections. A new method giving more precise results is presented. The proposed method is fully described, and results on real case studies are compared to existing watershed methods results.

关键词： 3d image segmentation Watershed transform

来源：评论

学校读者我要写书评

暂无评论

Where do Experts Look While doing 3d image segmentation 16

Where Do Experts Look While Doing 3D Image Segmentation

引用

9th Biennial ACM Symposium on Eye Tracking Research and Applications (ETRA)

作者： Sanandaji, Anahita Grimm, Cindy West, Ruth Parola, Max Kajihara, Meghan deutsch, Jeremy Carlew, Anne Yates, deniece Oregon State Univ Corvallis OR 97331 USA Univ North Texas Denton TX 76203 USA

ISBN: (纸本)9781450341257

3d image segmentation is a fundamental process in many scientific and medical applications. Automatic algorithms do exist, but there are many use cases where these algorithms fail. The gold standard is still manual segmentation or review. Unfortunately, even for an expert this is laborious, time consuming, and prone to errors. Existing 3d segmentation tools do not currently take into account human mental models and low-level perception tasks. Our goal is to improve the quality and efficiency of manual segmentation and review by analyzing how experts perform segmentation. As a preliminary step we conducted a field study with 8 segmentation experts, recording video and eye tracking data. We developed a novel coding scheme to analyze this data and verified that it successfully covers and quantifies the low-level actions, tasks and behaviors of experts during 3d image segmentation.

关键词： 3d image segmentation perception coding scheme

来源：评论

学校读者我要写书评

暂无评论

MdA-NET: MULTI-dIMENSIONAL ATTENTION-BASEd NEURAL NETWORK FOR 3d image segmentation 18

MDA-NET: MULTI-DIMENSIONAL ATTENTION-BASED NEURAL NETWORK FO...

引用

18th IEEE International Symposium on Biomedical Imaging (ISBI)

作者： Gandhi, Rutu Hong, Yi Univ Georgia Inst Artificial Intelligence Athens GA 30602 USA Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9781665412469

Segmenting an entire 3d image often has high computational complexity and requires large memory consumption;by contrast, performing volumetric segmentation in a slice-by-slice manner is efficient but does not fully leverage the 3d data. To address this challenge, we propose a multi-dimensional attention network (MdA-Net) to efficiently integrate slice-wise, spatial, and channel-wise attention into a U-Net based network, which results in high segmentation accuracy with a low computational cost. We evaluate our model on the MICCAI iSeg and IBSR datasets, and the experimental results demonstrate consistent improvements over existing methods.

关键词： Attention network 3d image segmentation Squeeze and excitation block

来源：评论

学校读者我要写书评

暂无评论

Automatic 3d image segmentation Using Adaptive k-means on Brain MRI

Automatic 3D Image Segmentation Using Adaptive <i>k</i>-mean...

引用

International Conference on Informatics Engineering and Information Science (ICIEIS 2011)

作者： Nieddu, Luciano Manfredi, Giuseppe d'Acunto, Salvatore Univ LUSPIO Fac Econom I-00145 Rome Italy Giustino Fortunato Univ Benevento Italy

ISBN: (纸本)9783642254529;9783642254536

The aim of this paper is to present a fully automatic adaptive k-means segmentation algorithm for MR images in a 3d space. We model the gray scale values of the 3d image with a White Gaussian Process and superimpose a prior model on the region process in the form of Markov Random Field. These assumptions require the use of estimators for the parameters of the two processes. This has been carried out using decreasing size windows. The Hammersley-Clifford theorem allows us to model the region process in term of a Gibbs distribution. The Gibbs parameter beta is estimated using a correlation-based technique. The segmentation is obtained maximizing the a posterior density function using an iterated Conditional Modes technique. The proposed algorithm is fully automatic, i.e. all the parameters of the model are estimated within the segmentation process.

关键词： Adaptive Estimation 3d image segmentation k-means Algorithm

来源：评论

学校读者我要写书评

暂无评论

3d image segmentation IMPLEMENTATION ON FPGA USING THE EM/MPM ALGORITHM

3D IMAGE SEGMENTATION IMPLEMENTATION ON FPGA USING THE EM/MP...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Yan Sun Lauren A. Christopher Department of Electrical and Computer Engineering Indiana University Purdue University Indianapolis IN 46202 USA

ISBN: (纸本)9781424442959;9781424442966

关键词： 3d image segmentation FPGA EM/MPM Field programmable gate arrays image segmentation Three-dimensional images Memory interface Computer hardware Iterative algorithms images algorithms

来源：评论

学校读者我要写书评

暂无评论

Automated 3d ultrasound image segmentation to aid breast cancer image interpretation

引用

ULTRASONICS 2016年 65卷 51-58页

作者： Gu, Peng Lee, Won-Mean Roubidoux, Marilyn A. Yuan, Jie Wang, Xueding Carson, Paul L. Nanjing Univ Dept Elect Sci & Engn Nanjing 210093 Peoples R China Univ Michigan Dept Radiol Ann Arbor MI 48109 USA

segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3d) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3d ultrasound volumes into three major tissue types: cyst /mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3d whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Breast ultrasound 3d image segmentation Assisted diagnosis Medical imaging

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：