Three-Dimensional Image Segmentation Based on Edge and Fuzzy Set Theory

罗立民; 鲍旭东; 谢筱华; 田雪芹

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Three-Dimensional Image Segmentation Based on Edge and Fuzzy Set Theory

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- Three-Dimensional Image Segmentation Based on Edge and Fuzzy Set Theory
- Acta Electronica Sinica Issue 9, (1995)
- 作者机构：
  
  东南大学生物科学与医学工程系图象研究室
- 作者简介：
- 基金信息：
- DOI：
  CLC： R445.2
- Published：1995
- 稿件说明：
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[1]罗立民,鲍旭东,谢筱华,田雪芹.基于边界和模糊集理论的三维图像分割[J].电子学报,1995(09):106-108+121.

罗立民, 鲍旭东, 谢筱华, et al. Three-Dimensional Image Segmentation Based on Edge and Fuzzy Set Theory[J]. Acta Electronica Sinica, 1995, (9).
[1]罗立民,鲍旭东,谢筱华,田雪芹.基于边界和模糊集理论的三维图像分割[J].电子学报,1995(09):106-108+121. DOI：

罗立民, 鲍旭东, 谢筱华, et al. Three-Dimensional Image Segmentation Based on Edge and Fuzzy Set Theory[J]. Acta Electronica Sinica, 1995, (9). DOI：

摘要

本文提出了一种基于边界和模糊集理论的三维图象分割方法，利用高斯－拉普拉斯算子检测出图象中各结构的边界后，通过区域增长获取感兴趣结构的三维二值模板，由高斯－拉普拉斯图象和二值模板出发，利用模糊集理论，确定感兴趣结构的三维模糊模板，从而达到在体积图象中分割出感兴趣结构的目的。

Abstract

This paper presents a three-dimensional image segmentaion method based on edge and fuzzy set theory. By using a Gauss-Laplacian operator

the edges of structures in the image are detected

then a region growing is applied to obtain the 3D binary mask of the volume of interest. From the Gauss-Laplacian image and the mask

the 3D fuzzy mask is determined and the volume of interest is then extracted.

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