Highly Robust Statistical Methods in Medical Image Analysis

被引：0

作者：

Kalina, Jan ^{[1
]}

机构：

[1] Acad Sci Czech Republ, Ctr Biomed Informat, Inst Comp Sci, CZ-18207 Prague 8, Czech Republic

来源：

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING | 2012年 / 32卷 / 02期

关键词：

robust statistics; classification; faces; robust image analysis; forensic science; COVARIANCE;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Standard multivariate statistical methods in medical applications are too sensitive to the assumption of multivariate normality and the presence of outliers in the data. This paper i devoted to robust statistical methods. In the context of medical image analysis they allow to solve the tasks of face detection and face recognition in a database of images. The result of the robust approaches in image analysis turn out to outperform those obtained with standard methods. Robust methods also have desirable properties appealing for practica applications, including dimension reduction and clear interpretability.

引用

页码：3 / 16

页数：14