title: Segmentation propagation using a 3D embryo atlas for high-throughput MRI phenotyping: comparison and validation with manual segmentation.
abstract: Effective methods for high-throughput screening and morphometric analysis are crucial for phenotyping the increasing number of mouse mutants that are being generated. Automated segmentation propagation for embryo phenotyping is an emerging application that enables noninvasive and rapid quantification of substructure volumetric data for morphometric analysis. We present a study to assess and validate the accuracy of brain and kidney volumes generated via segmentation propagation in an ex vivo mouse embryo MRI atlas comprising three different groups against the current "gold standard"--manual segmentation. Morphometric assessment showed good agreement between automatically and manually segmented volumes, demonstrating that it is possible to assess volumes for phenotyping a population of embryos using segmentation propagation with the same variation as manual segmentation. As part of this study, we have made our average atlas and segmented volumes freely available to the community for use in mouse embryo phenotyping studies. These MRI datasets and automated methods of analyses will be essential for meeting the challenge of high-throughput, automated embryo phenotyping.
authors.affiliation: Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom. f.norris@ucl.ac.uk
authors.forename: Francesca C
authors.initials: FC
authors.lastname: Norris
authors.forename: Marc
authors.initials: M
authors.lastname: Modat
authors.forename: Jon O
authors.initials: JO
authors.lastname: Cleary
authors.forename: Anthony N
authors.initials: AN
authors.lastname: Price
authors.forename: Karen
authors.initials: K
authors.lastname: McCue
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Scambler
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
authors.forename: Mark F
authors.initials: MF
authors.lastname: Lythgoe
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D004622:Embryo, Mammalian / Q000033:anatomy & histology*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D051379:Mice; D008953:Models, Anatomic; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D011296:Prenatal Diagnosis / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity