Segmentation of cell images based on improved graph MST and skeleton distance mapping

WANG Wei-xing; TIAN Li-ping; WANG Yue

doi:10.3788/OPE.20132109.2464

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Segmentation of cell images based on improved graph MST and skeleton distance mapping

更新时间：2020-08-12

- Segmentation of cell images based on improved graph MST and skeleton distance mapping
- Optics and Precision Engineering Vol. 21, Issue 9, Pages: 2464-2471(2013)
- 作者机构：
  
  福州大学物理与信息工程学院，福建福州 350000
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20132109.2464
  CLC： TP391.4
- Received：21 February 2013，
  
  Revised：06 April 2013，
  
  Published Online：30 September 2013，
  
  Published：15 September 2013
- 稿件说明：
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王卫星田利平王悦. 基于改进的图论最小生成树及骨架距离直方图分割细胞图像[J]. 光学精密工程, 2013,21(9): 2464-2471

WANG Wei-xing TIAN Li-ping WANG Yue. Segmentation of cell images based on improved graph MST and skeleton distance mapping[J]. Editorial Office of Optics and Precision Engineering, 2013,21(9): 2464-2471
王卫星田利平王悦. 基于改进的图论最小生成树及骨架距离直方图分割细胞图像[J]. 光学精密工程, 2013,21(9): 2464-2471 DOI： 10.3788/OPE.20132109.2464.

WANG Wei-xing TIAN Li-ping WANG Yue. Segmentation of cell images based on improved graph MST and skeleton distance mapping[J]. Editorial Office of Optics and Precision Engineering, 2013,21(9): 2464-2471 DOI： 10.3788/OPE.20132109.2464.

摘要

为了解决模糊且有粘连的细胞图像的难以分割问题，本文针对医学细胞图像的特点，应用图论的思想提出了一种图论与数学形态学结合的图像分割算法。该算法先对图像进行去噪和增强，然后用改进的图论最小生成树 (MST) 算法对细胞图像进行初始分割。改进的主要内容是在算法中引入了细胞尺寸和形状的信息，从而在一定程度上改善了图论算法过分割的缺陷。在进一步的图像分割中

为了解决二值图像中的细胞粘连问题，结合数学形态学的骨架边界距离信息找出分裂线将粘连细胞分离。与常规的分水岭算法完全不同，该算法没有重复性的运算。一系列细胞图像的试验表明，该算法能够很好地分割模糊且有粘连的细胞图像，其结果令人满意。

Abstract

To segment fuzzy and touching cell images accurately

an image segmentation algorithm based on graph theory and morphological mathematics was proposed according to the characteristics of medical cell images. With proposed algorithm

the images were smoothed and sharpened

firstly. Then

the improved Minimum Spanning Tree (MST) algorithm was used to segment the cell images

in which the cell size and shape information were added into MST graph to avoid the over-segmentation. Furthermore

the adherent cells were split by combining the distance mapping and the skeleton information in morphological mathematics to solve the problem of cell adhesion in the binary image. Different from the traditional watershed algorithms

the split algorithm has no repeat operation. By experiments

it shows that the proposed algorithm can segment fuzzy and touching cell images well and can obtain desired results.

关键词

Keywords

references

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