Stereo-assisted landmark detection for the analysis of changes in 3-D facial shape

Abstract

In this paper, a semi-automated approach to 3-D landmark digitization of the face is described which uses a combination of active shape model-driven feature detection and stereophotogrammetric analysis. The study aims to assess whether the proposed method is capable of detecting statistically significant changes in facial soft tissue shape due to mandibular repositioning in a cross-sectional patient sample. A hybrid stereophotogrammetric and structured-light imaging system is used for acquiring 3-D face models in the first instance. A landmark-based statistical analysis of facial shape change is then carried out using procrustes registration, principal component analysis and thin plate spline warping on the 2-D facial midline profiles and automatically digitized 3-D landmarks. The proposed method is validated both statistically and visually by characterizing shape changes induced by mandibular repositioning in a heterogeneous cross-sample of 20 orthodontic patients. It is shown that the method is capable of distinguishing between changes in facial morphology due to simulated surgical correction and changes due to other factors such as growth and normal variation within the patient sample. The study shows that the proposed method may be useful for auditing outcomes of clinical treatment or surgical intervention which result in changes to facial soft tissue morphology.

Application of three-dimensional reconstruction technology in dentistry: a narrative review

“…Subsequent studies have progressively complemented its powerful ability to measure soft tissue thickness [139] and accurately assess complex areas or dynamic soft tissue profiles [140,141]. In the field of scientific research, the step involving the extraction of 3D data of the face, many researchers [142][143][144][145][146][147][148][149][150][151][152][153] choose to use structured light technology or scanners based on this technology, reflecting its wide acceptance in dentistry. 3dMD system is one of the classic facial imaging devices used in dentistry.…”

Automatic recognition of surface landmarks of anatomical structures of back and posture

“…Because the mean local sets are found in different coordinate systems and come from different patients, the shape cannot be analyzed until the operations mentioned above are used: a full transformation (i.e., translation, rotation and scale) has to be calculated for every set. 52,53 In order to find the rotation and translation parameters, it suffices to use the Iterative Closest Point (ICP) technique. 54 The method for computing scale was based on, 55 which is calculated before other operations as follows:…”

Surgical Engineering in Cranio‐Maxillofacial Surgery: A Literature Review

“…The stages of the CAS workflow process for routine 3D virtual treatment planning of orthognathic surgery are the following: (1) image acquisition for 3D virtual orthognathic surgery, (2) processing of the acquired image data to construct a 3D virtual augmented model of the patient's head [47], (3) 3D virtual diagnosis of the patient [48], (4) 3D virtual treatment planning for the orthognathic surgery, (5) 3D virtual treatment planning communication, (6) 3D splint manufacturing, (7) 3D virtual treatment planning transfer to the OR, and (8) 3D virtual treatment outcome evaluation [49]. The image acquisition and processing of data for the 3D virtual treatment planning can merge information from bone (computed tomography (CT) scan, cone beam CT) [50,51], soft tissues [24,52], external facial appearance [53][54][55][56][57][58][59], 3D photographic system [57], and dental occlusion [47,[60][61][62][63] to provide the most complete 3D virtual model of each patient [64]. Figure 2 exhibits an example of CAS planning in orthognathic surgery.…”