基于类别方差的三维医学图像分割新方法

杜宇慧; 桂志国; 李晋华

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基于类别方差的三维医学图像分割新方法

更新时间：2026-09-14

- 基于类别方差的三维医学图像分割新方法
- 基于类别方差的三维医学图像分割新方法
- Issue 2, (2007)
- 作者机构：
  
  中北大学信息与通信工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2007
- 稿件说明：
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杜宇慧, 桂志国, 李晋华. 基于类别方差的三维医学图像分割新方法[J]. 2007, (2).
DOI：

杜宇慧, 桂志国, 李晋华. 基于类别方差的三维医学图像分割新方法[J]. 2007, (2). DOI：

摘要

提出一种交互式的三维医学图像分割算法.结合Otsu单阈值图像分割算法

提出了一种基于类别方差的双阈值分割算法.利用该算法对三维医学图像体数据的直方图进行了分析

最终得到的上下阈值使得分割结果具有最大类间方差.该算法采用迭代法实现

简单快速

且可保证分割出的组织包含目标组织.再对此阈值分割结果进行数学形态学的相关操作和三维区域生长

最终得到目标组织的准确分割和它的三维显示.实验证明

分割效果较好

三维重建满足要求.

Abstract

An interactive approach of 3D medical images segmentation was improved in this paper.Firstly

based on the Otsu′ single threshold segmentation method

a double-threshold segmentation method founded on class variance was proposed.It analyzed the histogram of volume data of 3D medical images

and then got two thresholds automatically that the result of segmentation had max variance between classes.This algorithm applying an iterative procedure was simple and fast

and ensured that the result included the goal tissue.Secondly

the 3D medical images segmented were processed by mathematical morphology operation and 3D region growing.Finally

the exact 3D segmentation and 3D visualization of goal tissue were achieved.The results of experiment show that the algorithm is feasible

and 3D reconstruction meets the goal.

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