Application of GAC Model Driven by the Local Entropy on Medical Image Segmentation

WANG Shun-feng; JI Xiao-na; ZHANG Jian-wei; CHEN Yun-jie; FANG Lin

doi:10.3969/j.issn.0372-2112.2013.12.026

您当前的位置：

首页 >

文章列表页 >

Application of GAC Model Driven by the Local Entropy on Medical Image Segmentation

更新时间：2025-07-16

- Application of GAC Model Driven by the Local Entropy on Medical Image Segmentation
- Acta Electronica Sinica Vol. 41, Issue 12, Pages: 2487-2492(2013)
- 作者机构：
  
  南京信息工程大学数学与统计学院,江苏,南京,210044
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2013.12.026
  CLC： ATP391
- Published：2013
- 稿件说明：
移动端阅览
WANG Shun-feng, JI Xiao-na, ZHANG Jian-wei, et al. Application of GAC Model Driven by the Local Entropy on Medical Image Segmentation[J]. Acta Electronica Sinica, 2013, 41(12): 2487-2492.
DOI：

WANG Shun-feng, JI Xiao-na, ZHANG Jian-wei, et al. Application of GAC Model Driven by the Local Entropy on Medical Image Segmentation[J]. Acta Electronica Sinica, 2013, 41(12): 2487-2492. DOI： 10.3969/j.issn.0372-2112.2013.12.026.

摘要

针对测地线活动轮廓（GAC）模型不能对包含噪声和灰度不均匀现象这类复杂背景图像成功提取目标的问题，本文提出局部熵驱动的GAC模型.首先提取图像的局部信息熵来刻画图像的灰度变化，再利用局部熵构造符号压力函数来指导轮廓曲线向目标边界靠近，实现目标的分割.为降低计算复杂度并提高模型对水平集变化的鲁棒性，采用二值水平集方法进行求解.实验结果表明，本文方法可以克服噪声和灰度不均匀对图像分割的影响，实现快速准确的分割.

Abstract

The geodesic active contour model(GAC)can't identify the object of the images with complex background such as noise and intensity inhomogeneities successfully.For this reason

this paper proposes GAC model driven by the local entropy.First of all

the local information entropy of image is abstracted to describe the local intensity variation.Then

the signed pressure force function based on the local entropy are structured

which guides the contour curve close to the boundary of the object and achieves the segmentation of the object.In order to reduce the computational complexity and improve the robustness of the proposed model to different level sets

the proposed method is implemented by the binary level set method.The experimental results show that this method can overcome the influence of complex background to the segmentation results

and realize fast and accurate segmentation.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Application of Local Entropy Algorithm on Clutter Tracking

Height Field TIN Representation Based on Local Entropy

Related Author

ZHANG Gong

ZHU Zhao-da

ZHOU Yi-nan

MING De-lie

YOU Ke-fei

TIAN Jin-wen

LIU Jian

Related Institution

College of Information Science and Technology,Nanjing University of Aeronautics and Astronautics

State Key Laboratory for Novel Software Technology, Nanjing University

Key Laboratory for Image Processing and Intelligent Control of the Education Department, Institute for Pattern Recognition and Artificial Intelligence,HUST

State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingJiangsu 210093China

Key Laboratory for Image Processing and Intelligent Control of the Education Department Institute for Pattern Recognition and Artificial IntelligenceHUSTWuhanHubei 430074China

⁰