3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation. S Moschoglou, S Ploumpis, MA Nicolaou et al.

Date: May 2019. Source: International Journal of Computer Vision (2020). https://doi.org/10.1007/s11263-020-01329-8. Abstract: Over the past few years, Generative Adversarial Networks (GANs) have garnered increased interest among researchers in Computer Vision, with applications including, but not limited to, image generation, translation, imputation, and super-resolution. Nevertheless, no GAN-based method has been proposed in the literature that can…

Integration of digital technology in the workflow for an osseointegrated implant-retained nasal prosthesis: A clinical report. L McHutchion, C Kincade, J Wolfaardt.

Date: May 2019. Source: The Journal of Prosthetic Dentistry, Volume 121, Issue 5, Pages 858-862. Abstract: This clinical report describes the integration of digital technology into the treatment of a patient with an osseointegrated implant-retained nasal prosthesis. The surgery was planned digitally to determine the optimal implant positions. Implant placement surgical guides were digitally designed…

EDAR, LYPLAL1, PRDM16, PAX3, DKK1, TNFSF12, CACNA2D3, and SUPT3H gene variants influence facial morphology in a Eurasian population. Y Li, W Zhao, D Li et al.

Date: April 2019. Source: Human Genetics 138, 681–689 (2019). https://doi.org/10.1007/s00439-019-02023-7. Abstract: In human society, the facial surface is visible and recognizable based on the facial shape variation which represents a set of highly polygenic and correlated complex traits. Understanding the genetic basis underlying facial shape traits has important implications in population genetics, developmental biology, and…

MeshMonk: Open-source large-scale intensive 3D phenotyping. JD White, A Ortega-Castrillón, H Matthews et al.

Date: April 2019. Source: Scientific Reports 9, 6085. https://doi.org/10.1038/s41598-019-42533-y. Abstract: Dense surface registration, commonly used in computer science, could aid the biological sciences in accurate and comprehensive quantification of biological phenotypes. However, few toolboxes exist that are openly available, non-expert friendly, and validated in a way relevant to biologists. Here, we report a customizable toolbox…

AMASS: Archive of Motion Capture as Surface Shapes. N Mahmood , N Ghorbani, NF Troje, G Pons-Moll, MJ Black.

Date: April 2019. Source: Cornell University Library – arXiv.org, Computer Vision and Pattern Recognition. Abstract: Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions limited, hampering progress on learning models of human motion. While there are many…

Linking the Expression of Facial Shape and BMI via the Hippo Signaling Pathway. S Ali, DE Ehrlich, LM Moreno Uribe, BA Amendt, MK Lee, JR Shaffer, ML Marazita, SM Weinberg, SF Miller.

Date: April 2019. Source: The FASEB Journal, Vol. 33, No. 1_supplement. Abstract: Obesity rates have more than tripled in children and adolescents in recent years. While many studies have examined the relationship between obesity and chronic illnesses, the impact of obesity on craniofacial form is less understood. Research in this area has suggested that obesity…

A Morphometric Assessment of the Influence of EGCG on Down Syndrome Facial Morphology. J Cintron, M Dierssen, R Gonzalez, J Sharpe, N Martinez-Abadias, J Starbuck.

Date: April 2019. Source: The FASEB Journal, Vol 33, No. 1_supplement. Abstract: Down syndrome (DS) is a genetic birth defect that results from Trisomy 21, which causes an overexpression of human chromosome 21 (HSA21) genes. Overexpressed HSA21 genes disturb development by altering morphogenesis and growth, resulting in cognitive impairment, characteristic facial morphology, and many other…

MeshGAN: Non-linear 3D Morphable Models of Faces. S Cheng, M Bronstein, Y Zhou, I Kotsia, M Pantic, S Zafeiriou.

Date: April 2019. Source: Cornell University Library – arXiv.org, Computer Vision and Pattern Recognition. Abstract: Generative Adversarial Networks (GANs) are currently the method of choice for generating visual data. Certain GAN architectures and training methods have demonstrated exceptional performance in generating realistic synthetic images (in particular, of human faces). However, for 3D object, GANs still…

Quantitative evaluation of local head malformations from 3 dimensional photography: application to craniosynostosis. L Tu, AR Porras, A Oh, N Lepore, GC Buck, D Tsering, A Enquobahrie, R Keating, GF Rogers, MG Linguraru.

Date: March 2019. Source: Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 1095035. Abstract: The evaluation of head malformations plays an essential role in the early diagnosis, the decision to perform surgery and the assessment of the surgical outcome of patients with craniosynostosis. Clinicians rely on two metrics to evaluate the head shape: head circumference…

Three-dimensional Analysis of Nasolabial Soft Tissues While Smiling Using stereophotogrammetry (3dMD). M Parra, R Pardo, ZS Haidar et al.

Date: March 2019. Source: International Journal of Morphology, 37(1):232-236, 2019. Abstract: The nasolabial region is the central esthetic unit of the face and is considered one of the most important determinants of the facial esthetic. The facial morphometry of soft tissues is a very important tool in facial surgery. Advances have been made recently in…