Paper Info
Title
An Efficient Permutation Approach for Classical and Bioequivalence Hypothesis Testing of Biomedical Shape Study
Abstract
A new statistical permutation analysis method is presented in this paper to efficiently and accurately localize regionally specific shape differences between groups of 3D biomedical images. It can improve the system’s efficiency by approximating the permutation distribution of the test statistic with Pearson distribution series. This procedure involves the calculation of the first four moments of the permutation distribution, which are derived theoretically and analytically without any permutation. Furthermore,bioequivalence testing aims for practical significances between the two groups that are statistically significant with the shape differences larger than a desired threshold. Experimental results based on both classical and bioequivalence hypothesis tests using simulated data and real biomedical images are presented to demonstrate the advantages of the proposed approach.
Year
DOI
Venue
2008
10.1109/BMEI.2008.192
BMEI (2)
Keywords
Field
DocType
pearson distribution series,shape difference,efficient permutation approach,biomedical image,specific shape difference,bioequivalence testing,bioequivalence hypothesis testing,bioequivalence hypothesis test,new statistical permutation analysis,permutation distribution,biomedical shape study,real biomedical image,shape,statistical analysis,testing,hypothesis test,biomedical engineering,statistical significance,parametric statistics,statistical distributions,biomedical imaging,image analysis
Pattern recognition,Test statistic,Pearson distribution,Computer science,Permutation,Probability distribution,Parametric statistics,Artificial intelligence,Bioequivalence,Statistical hypothesis testing,Statistical analysis
Conference
ISSN
Citations 
PageRank 
1948-2914
0
0.34
References 
Authors
4
2
Name
Order
Citations
PageRank
Chunxiao Zhou151.45
Yongmei Wang223223.10