Affiliation of Author(s):
管理学院
Key Words:
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
Abstract:
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.
Paper Publications
