Abstract
3D facial landmarks are known to be diagnostically relevant biometrics for many genetic syndromes. The objective of this study was to extend a state-of-the-art image-based 2D facial landmarking algorithm for the challenging task of 3D landmark identification on subjects with genetic syndromes, who often have moderate to severe facial dysmorphia. The automatic 3D facial landmarking algorithm presented here uses 2D image-based facial detection and landmarking models to identify 12 landmarks on 3D facial surface scans. The landmarking algorithm was evaluated using a test set of 444 facial scans with ground truth landmarks identified by two different human observers. Three hundred and sixty nine of the subjects in the test set had a genetic syndrome that is associated with facial dysmorphology. For comparison purposes, the manual landmarks were also used to initialize a non-linear surface-based registration of a non-syndromic atlas to each subject scan. Compared to the average intra- and inter-observer landmark distances of 1.1 mm and 1.5 mm respectively, the average distance between the manual landmark positions and those produced by the automatic image-based landmarking algorithm was 2.5 mm. The average error of the registration-based approach was 3.1 mm. Comparing the distributions of Procrustes distances from the mean for each landmarking approach showed that the surface registration algorithm produces a systemic bias towards the atlas shape. In summary, the image-based automatic landmarking approach performed well on this challenging test set, outperforming a semi-automatic surface registration approach, and producing landmark errors that are comparable to state-of-the-art 3D geometry-based facial landmarking algorithms evaluated on non-syndromic subjects.
Highlights
Due to the diversity, complexity, and rarity of genetic syndromes, one of the primary difficulties in properly treating afflicted patients is recognizing their condition in the first place
The 444 3D facial scans used in the analysis presented here were acquired using a 3DMD
This study was conducted in accordance with the Declaration of Helsinki and ethics approval has been granted by the Conjoint Health Research Ethics Board (CHREB) at the University of Calgary
Summary
Complexity, and rarity of genetic syndromes, one of the primary difficulties in properly treating afflicted patients is recognizing their condition in the first place. Exome and genome sequencing have improved diagnostic procedures, genetic tests can be expensive, genetic experts are often scarce, wait times for genetic consultations can be long, and there are still many conditions for which a genetic test is not available. Families and patients affected by genetic diseases must sometimes proceed without even basic information regarding health and developmental outcomes, let alone tailored clinical care. Advancements in gene-based technologies are essential to improving diagnostic procedures but complementary strategies ought to be pursued as well. Computer-assisted phenotyping is one strategy that can make use of inexpensive and widely available technologies for rapid syndrome screening
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