Microcalcification Clusters Detection Based on Ensemble Learning
发布时间:2024-08-09
点击次数:
- 所属单位:
- 管理学院
- 发表刊物:
- CCCM2008(国际会议论文集)
- 关键字:
- 中文关键字:微钙化点;集成学习;特征提取,英文关键字:microcalcification;ensemble learning; feature extr
- 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 highpass 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.
- 备注:
- 张新生
- 第一作者:
- 张新生
- 论文类型:
- 期刊论文
- 卷号:
- 卷:1
- 期号:
- 期:
- 页面范围:
- 页:669-673
- 是否译文:
- 否
- 发表时间:
- 2008-08-01