LIVE CELL IMAGE SEGMENTATION

被引：144

作者：

WU, KN

GAUTHIER, D

LEVINE, MD

机构：

[1] Center for Intelligent Machines, McGill University, Montreal

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 1995年 / 42卷 / 01期

基金：

英国医学研究理事会;

关键词：

D O I：

10.1109/10.362924

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

A major requirement of an automated, real-time, computer vision-based cell tracking system is an efficient method for segmenting cell images, The usual segmentation algorithms proposed in the literature exhibit weak performance on live unstained cell images, which can be characterized as being of low contrast, intensity-variant, and unevenly illuminated. We propose a two-stage segmentation strategy which involves: If extracting an approximate region containing the cell and part of the background near the cell, and 2) segmenting the cell from the background within this region, The approach effectively reduces the influence of peripheral background intensities and texture on the extraction of a cell region The experimental results show that this approach for segmenting cell images is both fast and robust. ,

引用

页码：1 / 12

页数：12

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