Performance of single and multi-atlas based automated landmarking methods compared to expert annotations in volumetric microCT datasets of mouse mandibles

Background: here we present an application of advanced registration and atlas building framework dramms to the automated annotation of mouse mandibles through a series of tests using single and multi-atlas segmentation paradigms and compare the outcomes to the current gold standard,manual annotation. results: our results showed multi-atlas annotation procedure yields landmark precisions within the human observer error range. the mean shape estimates from gold standard and multi-atlas annotation procedure were statistically indistinguishable for both euclidean distance matrix analysis (mean form matrix) and generalized procrustes analysis (goodall f-test). further research needs to be done to validate the consistency of variance-covariance matrix estimates from both methods with larger sample sizes. conclusion: multi-atlas annotation procedure shows promise as a framework to facilitate truly high-throughput phenomic analyses by channeling investigators efforts to annotate only a small portion of their datasets. © 2015 young and maga.