Anthropometric accuracy of three-dimensional average faces compared to conventional facial measurements. Z Shan, R TC Hsung, C Zhang et al.
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Training AI, Wearing Tech,
and Imaging Health.
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This is a retrospective serial longitudinal study of consecutively enrolled infants from September 2012 to July 2016 with BCLP who underwent NAM before primary lip and nose reconstructive surgery.
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This study believes 3D printed templates usage increases time efficiency, improves the match of skin flaps in donor and recipient arms, and allows us to control the amount of skin surplus without skin flap tip necrosis. In these procedures where time is of the essence, this team believes pre-operative planning is imperative for its success.
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This study focused on developing a novel deep-learning (DL)-based algorithm to predict the virtual soft tissue profile after mandibular advancement surgery and comparing its accuracy with the mass tensor model (MTM).
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This study applied the transfer learning model with a convolutional neural network based on 3-dimensional (3D) contour line features to evaluate the facial symmetry before and after OGS. A total of 158 patients were recruited in a retrospective cohort study for the assessment and comparison of facial symmetry before and after OGS from January 2018 to March 2020. Three-dimensional facial photographs were captured by the 3dMD face system in a natural head position, with eyes looking forward, relaxed facial muscles, and habitual dental occlusion before and at least 6 months after surgery.
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