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

页码：794 / 799

页数：6

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