Microcalcification Clusters Detection Based on Ensemble Learning

被引：0
|
作者：
Zhang, Xin-Sheng [1 ]
Xie, Hua [2 ]
Niu, Ya-Ling [2 ]
机构：
[1] Xian Univ Arc & Tech, Sch Management, Xian, Shaanxi Prov, Peoples R China
[2] Xian Int Univ, Xian, Peoples R China
来源：
2008 ISECS INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT, VOL 1, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/CCCM.2008.311
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new microcalcification clusters (MCs) detection method in mammograms is proposed in this paper, which is based on a new ensemble learning method. The ground truth of MCs is assumed to be known as a priori. In our algorithm, each MCs is enhanced by a well designed high-pass filter. Then the 116 dimentional image features are extracted by the feature extractor and fed to the ensemble decision model. In image feature domain, the MCs detection procedure is formulated as a supervised learning and classification problem, and the trained ensemble model is used as a classifier to decide the presence of MCs or not. A large number of experiments are carried out to evaluate the proposed MCs detection algorithms. The experimental results illustrate its effectiveness.
引用
收藏
页码：669 / +
页数：2
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