A fusion of neural network based auto-associator and classifier for the classification of microcalcification patterns

被引：0
|
作者：
Panchal, R [1 ]
Verma, B [1 ]
机构：
[1] Univ Cent Queensland, Fac Informat & Commun, Rockhampton, Qld 4702, Australia
来源：
NEURAL INFORMATION PROCESSING | 2004年 / 3316卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a novel approach to combine a neural network based auto-associator and a classifier for the classification of microcalcification patterns. It explores the auto-associative and classification abilities of a neural network approach for the classification of microcalcification patterns into benign and malignant using 14 image structure features. The proposed technique used combination of two neural networks; auto-associator and classifier for classification of microcalcification. It obtained 88.1% classification rate for testing dataset and 100% classification rate for training dataset.
引用
收藏
页码：794 / 799
页数：6
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