A new multi-expert decision combination algorithm and its application to the detection of circumscribed masses in digital mammograms

被引：31

作者：

Constantinidis, AS ^{[1
]}

Fairhurst, MC ^{[1
]}

Rahman, AFR ^{[1
]}

机构：

[1] Univ Kent, Elect Engn Labs, Canterbury CT2 7NT, Kent, England

来源：

PATTERN RECOGNITION | 2001年 / 34卷 / 08期

关键词：

decision combination; medical image analysis; mammography;

D O I：

10.1016/S0031-3203(00)00088-1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new multiple expert fusion algorithm is introduced, designated the "augmented behaviour-knowledge space method". Most existing multiple expert classification methods rely on a large training dataset in order to be properly utilised. The proposed method effectively overcomes this problem as it exploits the confidence levels of the decisions of each classifier. It will be shown that this new approach is advantageous when small datasets are available, and this is illustrated in its application to the detection of circumscribed masses in digital mammograms, with very encouraging results. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

引用

页码：1527 / 1537

页数：11

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