title: Performance of single and multi-atlas based automated landmarking methods compared to expert annotations in volumetric microCT datasets of mouse mandibles.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, 1900 Ninth Ave, 98101 Seattle, WA USA.
authors.forename: Ryan
authors.initials: R
authors.lastname: Young
authors.affiliation: Division of Craniofacial Medicine, Department of Pediatrics, University of Washington, Seattle, WA USA ; Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, 1900 Ninth Ave, 98101 Seattle, WA USA ; Department of Oral Biology, University of Washington, Seattle, WA USA.
authors.forename: A Murat
authors.initials: AM
authors.lastname: Maga
keywords: Automated landmarking; Geometric morphometrics; Mandible; Multi-atlas segmentation; microCT