TY - JOUR
T1 - Sources of variation in the 3dMDface and Vectra H1 3D facial imaging systems
AU - White, Julie D.
AU - Ortega-Castrillon, Alejandra
AU - Virgo, Ciara
AU - Indencleef, Karlijne
AU - Hoskens, Hanne
AU - Shriver, Mark D.
AU - Claes, Peter
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - As technology advances and collaborations grow, our ability to finely quantify and explore morphological variation in 3D structures can enable important discoveries and insights into clinical, evolutionary, and genetic questions. However, it is critical to explore and understand the relative contribution of potential sources of error to the structures under study. In this study, we isolated the level of error in 3D facial images attributable to four sources, using the 3dMDface and Vectra H1 camera systems. When the two camera systems are used separately to image human participants, this analysis finds an upper bound of error potentially introduced by the use of the 3dMDface or Vectra H1 camera systems, in conjunction with the MeshMonk registration toolbox, at 0.44 mm and 0.40 mm, respectively. For studies using both camera systems, this upper bound increases to 0.85 mm, on average, and there are systematic differences in the representation of the eyelids, nostrils, and mouth by the two camera systems. Our results highlight the need for careful assessment of potential sources of error in 3D images, both in terms of magnitude and position, especially when dealing with very small measurements or performing many tests.
AB - As technology advances and collaborations grow, our ability to finely quantify and explore morphological variation in 3D structures can enable important discoveries and insights into clinical, evolutionary, and genetic questions. However, it is critical to explore and understand the relative contribution of potential sources of error to the structures under study. In this study, we isolated the level of error in 3D facial images attributable to four sources, using the 3dMDface and Vectra H1 camera systems. When the two camera systems are used separately to image human participants, this analysis finds an upper bound of error potentially introduced by the use of the 3dMDface or Vectra H1 camera systems, in conjunction with the MeshMonk registration toolbox, at 0.44 mm and 0.40 mm, respectively. For studies using both camera systems, this upper bound increases to 0.85 mm, on average, and there are systematic differences in the representation of the eyelids, nostrils, and mouth by the two camera systems. Our results highlight the need for careful assessment of potential sources of error in 3D images, both in terms of magnitude and position, especially when dealing with very small measurements or performing many tests.
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U2 - 10.1038/s41598-020-61333-3
DO - 10.1038/s41598-020-61333-3
M3 - Article
C2 - 32157192
AN - SCOPUS:85081588115
SN - 2045-2322
VL - 10
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 4443
ER -