Segmentation propagation using a 3D embryo atlas for high-throughput MRI phenotyping: Comparison and validation with manual segmentation
Corresponding Author
Francesca C. Norris
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Centre for Mathematics and Physics in the Life Sciences and EXperimental Biology (CoMPLEX), University College London, London, United Kingdom
UCL Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, The Paul O'Gorman Building, 72 Huntley Street, London WC1E 6DD, UK===Search for more papers by this authorMarc Modat
Centre for Medical Image Computing, Departments of Medical Physics and Bioengineering and Computer Science, University College London, London, United Kingdom
Search for more papers by this authorJon O. Cleary
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Department of Medical Physics and Bioengineering, University College London, London, United Kingdom
Search for more papers by this authorAnthony N. Price
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorKaren McCue
Molecular Medicine Unit, UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorPeter J. Scambler
Molecular Medicine Unit, UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorSebastien Ourselin
Centre for Medical Image Computing, Departments of Medical Physics and Bioengineering and Computer Science, University College London, London, United Kingdom
Dementia Research Centre, National Hospital for Neurology and Neurosurgery, London, United Kingdom
Search for more papers by this authorMark F. Lythgoe
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorCorresponding Author
Francesca C. Norris
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Centre for Mathematics and Physics in the Life Sciences and EXperimental Biology (CoMPLEX), University College London, London, United Kingdom
UCL Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, The Paul O'Gorman Building, 72 Huntley Street, London WC1E 6DD, UK===Search for more papers by this authorMarc Modat
Centre for Medical Image Computing, Departments of Medical Physics and Bioengineering and Computer Science, University College London, London, United Kingdom
Search for more papers by this authorJon O. Cleary
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Department of Medical Physics and Bioengineering, University College London, London, United Kingdom
Search for more papers by this authorAnthony N. Price
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorKaren McCue
Molecular Medicine Unit, UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorPeter J. Scambler
Molecular Medicine Unit, UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorSebastien Ourselin
Centre for Medical Image Computing, Departments of Medical Physics and Bioengineering and Computer Science, University College London, London, United Kingdom
Dementia Research Centre, National Hospital for Neurology and Neurosurgery, London, United Kingdom
Search for more papers by this authorMark F. Lythgoe
Centre for Advanced Biomedical Imaging, Department of Medicine and UCL Institute of Child Health, University College London, London, United Kingdom
Search for more papers by this authorAbstract
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. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.
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