Validating 3D face morphing towards improving pre-operative planning in facial reconstruction surgery

Abstract

ABSTRACT Pre-traumatic/pathologic 3D facial imaging is rarely available to guide craniofacial reconstruction. This study aims to independently validate the regional accuracy of a 3D morphable model to estimate face shapes from 2D photographs for craniofacial surgical planning. 3D shape estimates were generated using the Basel Face Model (BFM 2017) from 2D photographs of 100 multi-racial subjects in the Binghamton University 3D Facial Expression database. Accuracy was evaluated by the per-vertex Euclidean distance between the shape estimate and the true 3D scan within defined facial regions. The 3D estimates’ average RMS distance error across all facial regions was 2.68 ± 0.97 mm, based on photos analysed with 10,000 iterations. The eyes, cheek, chin, forehead and mouth regions fit within ~2.5 mm from the true face shape, representing only marginal perceptible error. The nose and temple regions had lower accuracy (~3.1 mm) for all subjects. Significant differences in the nose region were dependent on race (Caucasian: 2.4 mm, East-Asian: 4.8 mm) and sex (Male: 2.5 mm, Female: 3.6 mm). On average, 3D face shape estimates using the BFM yielded clinically acceptable accuracy sufficient for use in planning to guide several craniofacial reconstruction regions. However, in individual cases, considerable errors exceeded clinical limits.