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癌细胞显微图像分割与识别研究
引用本文:王洪元,石澄贤,曾生根,夏德深.癌细胞显微图像分割与识别研究[J].计算机工程与应用,2003,39(36):214-216.
作者姓名:王洪元  石澄贤  曾生根  夏德深
作者单位:1. 南京理工大学计算机系,南京,210094;江苏石油化工学院计算机系,常州,213016
2. 南京理工大学计算机系,南京,210094
基金项目:江苏省教育厅省属高校自然科学研究项目(编号:01KJB520004)
摘    要:文章采用竞争Hopfield神经网络的自动聚类分割方法从腹水脱落细胞显微图像中分割可疑细胞和可疑细胞核,提取癌细胞的15个形态特征,利用柔性BP神经网络分类器对腹水脱落癌细胞进行分类识别。通过对临床病例的检验分析,表明该方法能获得较高的诊断正确率。

关 键 词:图像分割与识别  竞争Hopfield神经网络  柔性BP神经网络
文章编号:1002-8331-(2003)36-0214-03
修稿时间:2003年1月1日

Research for the Cancer Cells Microscopic Image Segmentation and Recognition
Wang Hongyuan , Shi Chengxian , Zeng Shenggen Xia Deshen.Research for the Cancer Cells Microscopic Image Segmentation and Recognition[J].Computer Engineering and Applications,2003,39(36):214-216.
Authors:Wang Hongyuan  Shi Chengxian  Zeng Shenggen Xia Deshen
Affiliation:Wang Hongyuan 1,2 Shi Chengxian 1,2 Zeng Shenggen 1 Xia Deshen 11
Abstract:A competitive Hopfield neural network is used in this paper to segment suspected cell and nucleus from the complex background in the microscopic image of cells fallen into peritoneal effusion.15features of cancer cell are ab-stracted.These features are employed to construct a flexible BP neural network classifier,which classifies and recognizes the cancer cells fallen into peritoneal effusion.Tests are performed using clinic cases recommended by the pathologists,results show that the proposed algorithm can efficiently segment cell image and receive higher accuracy of cancer cell diagnosis.
Keywords:Image segmentation&recognition  Competitive Hopfield NN  Flexible BP NN  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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