DocumentCode
3261880
Title
A Better Classifier Based on Rough Set and Neural Network for Medical Images
Author
Yun, Jiang ; Zhanhuai, Li ; Yong, Wang ; Longbo, Zhang
Author_Institution
Coll. of Comput. Sci., Northwestern Polytech. Univ.
fYear
2006
fDate
Dec. 2006
Firstpage
853
Lastpage
857
Abstract
Detecting tumor in mammography is a difficult task because of complexity in the image. This brings the necessity of creating automatic tools to find whether a mammography present tumor or not. In this paper we integrate neural network with reduction of rough set theory which we call the rough neural network (RNN) to classify digital mammography. The experimental results show that the RNN performs better than purely using neural network in terms of time, and it can get 92.37% classifying accuracy which is higher than 81.25% using neural network only
Keywords
image classification; mammography; medical image processing; neural nets; rough set theory; tumours; digital mammography; medical image classification; rough neural network; rough set theory; tumor detection; Biomedical imaging; Breast cancer; Data mining; Educational institutions; Feature extraction; Mammography; Medical diagnostic imaging; Neoplasms; Neural networks; Recurrent neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2702-7
Type
conf
DOI
10.1109/ICDMW.2006.1
Filename
4063745
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