Abstract
BackgroundManual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results. However, the variability of human facial landmarks is only sparsely addressed in the current literature as opposed to e.g. the research fields of orthodontics and cephalometrics. We present a full facial 3D annotation procedure and a sparse set of manually annotated landmarks, in effort to reduce operator time and minimize the variance.MethodFacial scans from 36 voluntary unrelated blood donors from the Danish Blood Donor Study was randomly chosen. Six operators twice manually annotated 73 anatomical and pseudo-landmarks, using a three-step scheme producing a dense point correspondence map. We analyzed both the intra- and inter-operator variability, using mixed-model ANOVA. We then compared four sparse sets of landmarks in order to construct a dense correspondence map of the 3D scans with a minimum point variance.ResultsThe anatomical landmarks of the eye were associated with the lowest variance, particularly the center of the pupils. Whereas points of the jaw and eyebrows have the highest variation. We see marginal variability in regards to intra-operator and portraits. Using a sparse set of landmarks (n=14), that capture the whole face, the dense point mean variance was reduced from 1.92 to 0.54 mm.ConclusionThe inter-operator variability was primarily associated with particular landmarks, where more leniently landmarks had the highest variability. The variables embedded in the portray and the reliability of a trained operator did only have marginal influence on the variability. Further, using 14 of the annotated landmarks we were able to reduced the variability and create a dense correspondences mesh to capture all facial features.
Highlights
Manual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results
The inter-operator variability was primarily associated with particular landmarks, where more leniently landmarks had the highest variability
Analysis of facial morphology is based on facial distances i.e. the distance between facial landmarks [1,2,3] or on statistical models [1,4]
Summary
Manual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results. The variability of human facial landmarks is only sparsely addressed in the current literature as opposed to e.g. the research fields of orthodontics and cephalometrics. We present a full facial 3D annotation procedure and a sparse set of manually annotated landmarks, in effort to reduce operator time and minimize the variance. The systems have enabled more accurate and objective methods of capturing differences in facial morphology. The reliability of facial landmark annotation has not been as thoroughly studied as landmark annotations in other fields, e.g. cephalometry [7]. Buschang et al [8] assessed the inter-operator annotation variability of anatomical landmarks on the skull for use in orthodontics and cephalometric analysis, using ANOVA analysis. By Larsen et al the inter-operator annotation variance was included in the PCA when analyzing cranial growth [12]. The landmark variance was addressed using a weighting scheme giving most weight to annotation landmarks with low variance
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