A technique based on wavelet and morphology transform to recognize the cancer cell in pleural effusion

Author

Chen, Fuhua ; Xie, Jun ; Zhang, Hong ; Xia, Deshen

Author_Institution

Dept. of Comput., Nanjing Univ. of Sci. & Tech., China

fYear

2001

fDate

2001

Firstpage

199

Lastpage

203

Abstract

This paper analyzes the cause of cells fallen off into pleural effusion, and its effect on diagnosis of lung cancer. According to features of cancer cells in morphology and structure, the responding presentations in wavelet analysis and morphology are discussed. Some gray-scale features and gray-scale gradient features based on wavelet analysis, and some morphology features about edge intensity are presented. Based on these features a backpropagation neural network is constructed to recognize cancer cells fallen off into pleural effusion. Experimental results show that this method has a high recognition ratio

Keywords

backpropagation; cancer; lung; medical image processing; neural nets; wavelet transforms; backpropagation neural network; cancer cell recognition; edge intensity; experimental results; gray-scale features; gray-scale gradient features; lung cancer diagnosis; medical image processing; morphology transform; pleural effusion; wavelet analysis; Biomedical imaging; Cancer; Cause effect analysis; Computer vision; Continuous wavelet transforms; Discrete wavelet transforms; Image analysis; Morphology; Neural networks; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Medical Imaging and Augmented Reality, 2001. Proceedings. International Workshop on

Conference_Location

Shatin, Hong Kong

Print_ISBN

0-7695-1113-9

Type

conf

DOI

10.1109/MIAR.2001.930286

Filename

930286