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Full-Text Articles in Medicine and Health Sciences
Direct Comparison Of Feature Tracking And Autocorrelation For Velocity Estimation, Gregory R. Bashford, Derek J. Robinson
Direct Comparison Of Feature Tracking And Autocorrelation For Velocity Estimation, Gregory R. Bashford, Derek J. Robinson
Biomedical Imaging and Biosignal Analysis Laboratory
Feature tracking is an algorithm for estimating tissue motion and blood flow using pulse-echo ultrasound. It was proposed as a computationally simpler alternative to other techniques such as autocorrelation and time-domain cross correlation. The advantage of feature tracking is that it selectively extracts easily identifiable parts of the speckle signal (e.g., the local maxima), reducing the amount of information being processed. Studies on feature tracking to date have used stationary, specklegenerating targets to simulate blood flow. Also, feature tracking has not been compared with accepted commercial methods. This study directly compares feature tracking performance with the complex autocorrelation method, which …
Bioinformatics In The 21st Century, Heather G. Kuruvilla
Bioinformatics In The 21st Century, Heather G. Kuruvilla
Science and Mathematics Faculty Publications
No abstract provided.
Power Boosting In Genome-Wide Studies Via Methods For Multivariate Outcomes, Mary J. Emond
Power Boosting In Genome-Wide Studies Via Methods For Multivariate Outcomes, Mary J. Emond
UW Biostatistics Working Paper Series
Whole-genome studies are becoming a mainstay of biomedical research. Examples include expression array experiments, comparative genomic hybridization analyses and large case-control studies for detecting polymorphism/disease associations. The tactic of applying a regression model to every locus to obtain test statistics is useful in such studies. However, this approach ignores potential correlation structure in the data that could be used to gain power, particularly when a Bonferroni correction is applied to adjust for multiple testing. In this article, we propose using regression techniques for misspecified multivariate outcomes to increase statistical power over independence-based modeling at each locus. Even when the outcome …