Multiclass detection of cells in multicontrast composite images.

Multiclass detection of cells in multicontrast composite images.
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DOI:
10.1016/j.compbiomed.2009.11.013
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发表时间:
2010-02
影响因子:
7.7
通讯作者:
Yao, Y. Lawrence
Yao, Y. Lawrence
中科院分区:
工程技术2区
文献类型:
--
作者:
Long, Xi;Cleveland, W. Louis;Yao, Y. Lawrence

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In this paper, we describe a framework for multiclass cell detection in composite images consisting of images obtained with three different contrast methods for transmitted light illumination (referred to as multicontrast composite images). Compared to previous multiclass cell detection results, the use of multicontrast composite images was found to improve the detection accuracy by introducing more discriminatory information into the system. Preprocessing multicontrast composite images with Kernel PCA was found to be superior to traditional linear PCA preprocessing, especially in difficult classification scenarios where high-order nonlinear correlations are expected to be important. Systematic study of our approach under different overlap conditions suggests that it possesses sufficient speed and accuracy for use in some practical systems.
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