학술논문
Learning a nonlinear color distance metric for the identification of skin immunohistochemical staining
Document Type
Conference
Author
Source
2009 22nd IEEE International Symposium on Computer-Based Medical Systems Computer-Based Medical Systems, 2009. CBMS 2009. 22nd IEEE International Symposium on. :1-7 Aug, 2009
Subject
Language
ISSN
1063-7125
Abstract
This paper presents a semiautomatic method for the identification of immunohistochemical (IHC) staining in digitized samples. The user trains the system by selecting on a sample image some typical positive stained regions that will be used as a reference for the construction of a distance metric. In this learning process, the global optimum is obtained by induction employing higher polynomial terms of the Mahalanobis distance, extracting nonlinear features of the IHC pattern distributions. The results of the proposed method showed a high correlation to a pathologist's manual analysis, which was used as a golden standard, presenting a more robust discrimination between stained and non-stained areas with little bias.