An exploratory study of bust measurements during running using 4D scanning technology. J Pei, L Griffin, SP Ashdown, J Fan, B Juhnke, C Curry.

3dMD Customer Research, Human Factors | Anthropometric, Size & Fit | Wearable Tech | Apparel | Product Design, 3dMDbody, Apparel

The purpose of this research was to introduce the use of 4D scanning technology to understand breast shape in motion. Twenty-six female participants who identified themselves as wearing Missy Size 18 were recruited for scanning. Three most common bust measurements were tracked in dynamic states and compared with the static state.

Three-Dimensional Nasolabial Changes After Nasoalveolar Molding and Primary Lip/Nose Surgery in Infants With Bilateral Cleft Lip and Palate. L Mancini, S Avinoam, BH Grayson, RL Flores, DA Staffenberg, PR Shetye.

3dMD Customer Research, Genetics, Medical, 3dMDface, Craniofacial/Cleft, Plastics

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.

Designing and utilizing 3D-printed skin incision guides during the first Dutch bilateral hand-arm transplantation. S Hummelink, AS Kruit, SER Hovius, DJO Ulrich.

3dMD Customer Research, Medical, Size & Fit | Wearable Tech | Apparel | Product Design, 3D Printing, 3dMDbody

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.

Three-dimensional virtual planning in mandibular advancement surgery: soft tissue prediction based on deep learning. R ter Horst, H van Weert, T Loonen, S Bergé, S Vinayahalingam, F Baan, T Maal, G de Jong, T Xi.

3dMD Customer Research, Computer Science | Computer Vision, Medical, 3dMDface, Oral and Maxillofacial, Orthognathic

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).