中国组织工程研究

中国组织工程研究 ›› 2010, Vol. 14 ›› Issue (39): 7371-7373.doi: 10.3969/j.issn.1673-8225.2010.39.037

• 骨与关节综述 bone and joint review • 上一篇    下一篇

人工神经网络在染色体自动分析系统中的应用

闫文忠1，封孝辉2   

  1. 华北科技学院，1计算机系，2机电工程系，北京市 101601
  • 出版日期:2010-09-24 发布日期:2010-09-24
  • 作者简介:闫文忠☆，男，1976年生，河南省焦作市人，汉族， 2008年北京邮电大学毕业，博士，讲师，主要从事数字图像处理研究。 yanwenzhong@ncist.edu.cn

Application of artificial neural network in chromosome automatic analysis system

Yan Wen-zhong1, Feng Xiao-hui2   

  1. 1 Department of Computer, 2 Department of Mechanical and Electrical Engineering, North China Institute of Science and Technology, Beijing  101601, China　
  • Online:2010-09-24 Published:2010-09-24
  • About author:Yan Wen-zhong☆, Doctor, Lecturer, Department of Computer, North China Institute of Science and Technology, Beijing 101601, China yanwenzhong@ncist.edu.cn

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593

被引次数

2

摘要：

背景：人体染色体的分类与识别是医学遗传学中的一项基本任务，应用计算机技术实现人体染色体自动分析与识别是人体染色体图像分析技术的重要研究课题。
目的：介绍人工神经网络的基本原理、技术优势、应用方法，研究人工神经网络在染色体自动分析系统中应用。
方法：由第一作者检索1994/2009 EBSCO数据(http://search.ebscohost.com)及万方数据库(http://www. wanfangdata.com.cn)有关人工神经网络在染色体自动分析系统中应用方面的文献，英文检索词为“chromosome，artificial neural network”，中文检索词为“染色体，人工神经网络”。
结果与结论：研究染色体自动分析系统的目的，就是要减轻技术人员的劳动强度，使他们从繁琐的重复劳动中解放出来，并最终将这些系统应用于临床，进行肿瘤患者的细胞遗传学鉴定、优生优育的检查等工作。尽管神经网络在染色体自动分析系统中的应用已经经过了多年的发展与完善，但仍存在一定的局限性：①它首先需要一套准确无误的已分类染色体数据库，这对一般研究人员来说是不易得到的。②分类的结果不够准确，甚至达不到训练有素的细胞学研究者的水平。③神经网络有它固有的缺点——训练数据量庞大、训练时间长。因此在今后的研究中，应该从优化神经网络的结构、提取有效特征、减少不必要的运算着手，继续改进和完善这个网络。

关键词: 人工神经网络, 染色体自动分析, 分类, 数字化神经医学, 综述文献

Abstract:

BACKGROUND: The classification and identification of human chromosome is a basic mission of medical genetics. Analyzing and identifying human chromosome automatically with computer technology is an important research subject in human chromosome image analysis.
OBJECTIVE: To introduce basic principle, technique advantages and operating methods of artificial neural network and explore the applications of artificial neural network in chromosome automatic analysis.
METHODS: A computer-based online search of EBSCO database (http://search.ebscohost.com) and Wanfang database (http://www.wanfangdata.com.cn) was performed for articles about application of artificial neural network in chromosome automatic analysis system with the key words “chromosome, artificial neural network” in English and Chinese.
RESULTS AND CONCLUSION: The aim of studying chromosome automatic analysis is to reduce technician labor intensity and allow them free from repeated laboring. Finally, these systems are used in clinic for molecular cytogenetics identification and aristogenesis etc. Despite the significant research effort and progress of applications of artificial neural network in chromosome automatic analysis over these years, there are still some localizations. The classified chromosome database is needed, which is not easy to get for general researchers. In addition, the accuracy of the classification result is not good enough, which even cannot reach the level of well-trained cytology researchers. Moreover, the neural network has its inherent shortcomings such as huge training data and huge training time. Therefore, further research and development is required to improve and consummate the network through optimizing network structure, selecting effective characteristic, and reducing otiose operation.

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