- Email: [email protected]
Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging
Accepted Manuscript Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging Jesper Jared Secher, DDS, PhD-student, Tron Andre Darvann, MSc, PhD, Research Engineer, Else Marie Pinholt, DDS, Professor, Consultant, MSci, Dr Odont. PII:
S1010-5182(17)30244-5
DOI:
10.1016/j.jcms.2017.07.006
Reference:
YJCMS 2729
To appear in:
Journal of Cranio-Maxillo-Facial Surgery
Received Date: 13 April 2017 Revised Date:
15 June 2017
Accepted Date: 18 July 2017
Please cite this article as: Secher JJ, Darvann TA, Pinholt EM, Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging, Journal of Cranio-Maxillofacial Surgery (2017), doi: 10.1016/j.jcms.2017.07.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging
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Jesper Jared Secher1,2, DDS, PhD-student Tron Andre Darvann3, MSc, PhD, Research Engineer
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Else Marie Pinholt1, 2, DDS, Professor, Consultant, MSci, Dr Odont.
1: Department of Oral and Maxillofacial Surgery, Hospital of South West Denmark,
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Finsensgade 35, DK - 6700 Esbjerg, Denmark.
2: University of Southern Denmark, Faculty of Health, Institute for Regional Services Sciences, Winsløwparken 19, 3. 5000 Odense C, Denmark.
3: University of Copenhagen, Department of Odontology, 3D Craniofacial Image
Corresponding author
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Dr. Jesper Jared Secher
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Research Laboratory, 20, Nørre Allé, DK-2200 Copenhagen N, Denmark.
Department of Oral and Maxillofacial Surgery
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Hospital of South West Denmark, Finsensgade 35, DK - 6700 Esbjerg, Denmark Telephone: (+45) 40269517 E-mail address: [email protected]
ACCEPTED MANUSCRIPT Summary
Purpose: A prospective study was performed to test the accuracy and reproducibility of
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the DAVID-SLS-2 scanner (SLS-2) [DAVID Vision Systems GmbH], compared to the validated 3dMDtrio scanner (3dMD) [3dMD, LLC, Atlanta, GA, USA].
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Materials and Methods: The accuracy of the SLS-2 was determined through multiple scans of a mannequin face model using both scanners. The reproducibility of a protocol
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for achieving consistent three-dimensional (3D) face scans in live subjects was carried out using the SLS-2. A precision of <1 mm was considered clinically significant.
Results: The mannequin face model was reproduced with no significant errors in the
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SLS-2 compared to the 3dMDtrio, with normally distributed data (mean = 0.002 mm; SD = 0.01 mm). In live subjects, the forehead, midface, chin and general face region showed mean errors and SD < 0.24 mm and < 1 mm, respectively. In the neck area, the
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data were not found to be normally distributed (mean = −1.6 mm; SD = 2.1 mm).
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Conclusion: Structured light scanning may be used for acquiring 3D face scans in live subjects in a radiation-free and reproducible manner, provided that the head of the subject is positioned in the same posture for each scan. Special care is recommended in positioning the head in the sagittal plane during scanning.
Keywords: structured light scanning, 3D photogrammetry, accuracy, reproducibility
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ACCEPTED MANUSCRIPT INTRODUCTION The use of three-dimensional (3D) images to reproduce facial surfaces in cranio- and maxillofacial surgery has been shown to be a valuable perioperative tool (Rana, Gellrich
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et al., 2011; Meulstee, Liebregts et al., 2015; Ostwald, Berssenbrugge et al., 2015). A high level of accuracy and reproducibility in 3D imaging is crucial for clinical and research purposes. Reportedly, a mean error < 1 mm is considered to be clinically
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significant (Maal, van Loon et al., 2010; Hammoudeh, Howell et al., 2015; Nord, Ferjencik et al., 2015; Zinser and Zoeller, 2015; Ye, Lv et al., 2016).
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Sources of 3D surface imaging are represented primarily by the non-ionizing modalities of laser scanning, structured light scanning (SLS) and 3D stereophotogrammetry. Structured light scanners emit light within visible wavelengths as opposed to laser light of the classic laser scanner. Previously, SLS systems have been classified as laser type
advances.
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scanners, but have emerged as a scanning modality of their own due to recent technical
Three-dimensional stereophotogrammetry uses simultaneous multi-angle photography
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to create a 3D model, and is currently considered the gold standard in facial surface imaging due to fast image acquisition times in combination with a high level of
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reliability and precision (Wong, Oh et al., 2008; Maal, van Loon et al., 2010; Nord, Ferjencik et al., 2015; Hermann, Darvann et al., 2016). Three-dimensional stereophotogrammetry is considerably more expensive compared to laser scanning and SLS, but is less prone to motion artifacts due to image acquisition times measured in milliseconds in contrast to seconds in laser scanning and SLS. The latter may also require multiple scans from various angles, as a single sensor is common in these systems, in contrast to a single image acquisition in 3D stereophotogrammetry.
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ACCEPTED MANUSCRIPT Despite the obvious advantages of 3D photogrammetry, new SLS scanners are frequently being developed, and the quality gap between the two imaging modalities is closing, as shown in recent studies (Kim, Jung et al., 2015; Modabber, Peters et al.,
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2016; Ye, Lv et al, 2016; Rodriguez-Florez, Goktekin et al., 2017). In combination with a considerably lower price compared to 3D stereo-photogrammetry, SLS may offer an
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alternative from a cost-effectiveness point of view.
The aim of this study was to determine the following: (1) the accuracy and
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reproducibility of a modern SLS scanner compared to an established 3D photogrammetric system in a mannequin face model; and (2) the reproducibility of a scanning protocol designed for scanning live human faces over time using the SLS
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scanner.
MATERIALS AND METHODS
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Subjects and scanners
Two experiments, A and B, were performed. In experiment A, the face of a mannequin
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torso was scanned. The mannequin head contained four face markers and eyelashes irrelevant to this study, and were therefore digitally masked out prior to image measurement. Experiment B included 10 healthy human study subjects, eight female and two male, who signed a consent form prior to participation in the study. The scanner to be tested was the DAVID-SLS-2, DAVID Vision Systems GmbH (SLS2). In experiment A, the results of the SLS-2 were compared to the results of the 3dMDtrio system, 3dMD, Atlanta, GA, USA (3dMD).
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ACCEPTED MANUSCRIPT Important practical differences between the two systems consist of image acquisition time and the cost of the scanners. The SLS-2 requires three scans to cover the full-face region from ear to ear, with 4-10 seconds per image, compared to 1.5 milliseconds for a
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single scan in the 3dMD. The test scanner SLS-2 is priced at around $3000, compared to the 3dMD at $20,000-50,000. Further technical specifications are listed in Table 1.
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Ethics considerations
The principles of the Declaration of Helsinki were observed throughout the experiment.
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The study was granted exemption by the local institutional review board. Written informed consent was obtained from the study participants according to local ethical and data management regulations.
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Experiment A
The accuracy of the SLS-2 (Figure 1) was determined by 30 consecutive scans of the mannequin face. In order to obtain similar coverage of the face from ear to ear as in the
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3dMD scanner (Figure 2), the mannequin was repositioned three times in between the acquisitions in the SLS-2 (Figure 3a). Immediately after image acquisition, the three
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scans were fused together using the accompanying software “Shape Fusion” (DAVID 3D Solutions GbR, Braunschweig, Germany). An average processing time of 5-10 minutes was required to complete a full-surface reconstruction of the face using the default settings in “Shape Fusion.” The process was semi-automatic and involved manual input in terms of selecting the scans and the order in which to fuse them into one model.
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ACCEPTED MANUSCRIPT A reference face (Figure 3b) was constructed by averaging 30 3dMD scans taken of the mannequin on the same day. The mannequin was repositioned before each acquisition for all 30 acquisitions. An iterated closest point (ICP) algorithm was used in order to
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bring the 30 scans into best alignment before averaging. Before a meaningful averaging could be carried out, detailed point correspondence had to be established among all 30 scans. The following standard algorithm was used: (1) Pick a reference scan at random
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among the 30 aligned scans. (2) For each surface point on the reference scan, determine the closest location on the 29 other scans; use these as anatomically corresponding
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locations across all scans. (3) Calculate pointwise arithmetic mean to form a new reference face. (4) In order to minimize bias towards the shape of the originally chosen reference scan, repeat the above procedure (steps 2 and 3) using the new reference shape. The reference face was subsequently segmented into seven regions comprising
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the forehead, eyes, nose, mouth, cheek, chin and neck (Figure 3c-d) by fitting a presegmented standard face atlas to the reference face by non-rigid surface registration (Szeliski and Lavallee, 1994; Rueckert, Sonoda et al., 1999; Rueckert, Frangi et al.,
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2003).
Each of the 30 SLS-2 face scans was in turn compared to the reference face by
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calculating, at every surface point of the SLS-2 surface, the distance to the closest location on the reference face after achieving optimal overall spatial alignment between the two using the Iterated Closest Point algorithm (ICP) (Zhang, 1994). The ICP algorithm resulted in 30 distance maps that was color-coded onto the reference face for visual inspection of the spatial distribution of distances for each of the 30 scans. The distance was given a sign depending on whether the SLS-2 scan was inside (negative) or outside (positive) of the reference face. Histograms of distances were calculated for
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ACCEPTED MANUSCRIPT each of the seven face regions as well as for the full-face region, the latter consisting of the union of the seven regions. Mean histograms were also calculated, representing the distribution of differences in all 30 distance maps. The mean of the distribution was
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used as a measure of systematic error. A mean different from zero would reveal that the SLS-2 scanner under- or overestimated true dimensions. The standard deviation (SD) of the distribution provided another measure of the error of the SLS-2. The maximum
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difference was calculated, as well as the difference where 95% of surface points were
included. Finally, entities pertaining to the cumulative histogram were calculated as the
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percentage of points with a difference larger than a given limit. Two limits were chosen and tabulated: 0.5 mm and 1.0 mm respectively. To calculate and display a distance map representing the mean of all 30 distance maps, it was necessary to establish a detailed point correspondence between all surfaces. This was achieved by fitting a face
1994).
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Experiment B
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atlas to all surfaces by use of non-rigid surface registration (Szeliski and Lavallee,
Ten live subjects were scanned twice consecutively in the SLS-2. The subjects were
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seated with their heads on a headrest, slightly tilted back and with their teeth in maximal intercuspidal position (Figure 4). The head posture was aligned according the vertical midline of the face, and the degree of the head tilt was secured by positioning the head of the study subject so that a horizontal line intersected the lateral corner of the nose and the intertragic notch in either side. This was done to avoid blank areas due to the single sensor of the SLS-2 and was guided by the horizontal grid lines of the scanner window on the personal computer (PC) monitor.
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ACCEPTED MANUSCRIPT Three SLS-2 scans were needed for a full face scan consisting of a frontal scan perpendicular to the midline of the face and bilateral scans spaced approximately 45-55° measured from the facial midline (Figure 4).
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Time was provided for subjects to walk and talk between the two sessions, simulating two independent visits to the photographer. Before each of the two acquisitions, the chair and headrest were readjusted and the subject was instructed to keep a relaxed,
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neutral expression during the scan.
Spatial differences were quantified in each surface point as the closest distance between
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the two acquired surfaces after the two surfaces had been brought into an optimal spatial alignment using ICP on a subregion of the face comprising the lower part of the forehead and the upper part of the bridge of the nose. This subregion was chosen because it could be assumed to be largely unaffected by variation in facial expression.
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The distance values were color-coded onto one of the surfaces for inspection of spatial distribution. Histograms of distances were calculated for each subject and each of the seven face regions, as well as for the full-face region. Mean histograms for all subjects
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and regions were calculated in a similar way as for experiment A. As for experiment A, a mean, SD, maximum 95% cutoff and percentage of points with
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distances larger than given limits were calculated. To investigate the spatial distribution of mean differences in the whole population of subjects, it was necessary to establish a detailed point correspondence between individual distance maps. This was achieved by deforming a face atlas to each subject face using an automatic method (Szeliski and Lavallee 1994, Rueckert, Sonoda et al. 1999, Rueckert, Frangi et al. 2003) initialized by four manually placed landmarks on (1) the right and (2) the left ear at the junction between the tragus and the crus of the helix, (3) the sellion, and (4) the pronasale. The
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ACCEPTED MANUSCRIPT face atlas contained the seven face regions shown in Figure 3c-d, and these were transferred to each of the subjects by the deformation.
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Data handling Surface registration and visualization of results in terms of color-coded surfaces were performed in the software package “Landmarker” developed in-house based on VTK
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(William Scroeder 1996, Tron Andre Darvann 2008). Descriptive statistics and
histogram calculations were performed in IDL (Interactive Data Language, Research
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Systems Inc., Boulder, CO, USA). Atlas deformation was performed in the Image Registration Tool Kit (IRTK) software developed by Daniel Rueckert, Imperial College
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London, UK, under a license to Ixico Ltd.
RESULTS
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Experiment A
Figure 5 shows mean histograms of differences (distances expressed in millimeters)
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among all 30 mannequin face scans and the reference face for the full-face region as well as for each of the seven face regions separately. All histograms are reasonably normally distributed, with mean values close to zero and with varying but small standard deviations, as reflected in Table 2. The SD is 0.1 mm for the whole face, whereas it varies between 0.07 mm (forehead) and 0.27 mm (eye region) for the seven face regions. Figure 6 provides a display of the magnitude and spatial distribution of the distances with the reference surface shown as color-coded in terms of (1) the mean of
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ACCEPTED MANUSCRIPT the absolute values of distances, (2) the SD of the distances, and (3) the maximum distance in each surface point. The spatial coverage of the SLS-2 scanner is demonstrated to be smaller than the 3dMD but still covering the full-face region,
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including the ears.
Experiment B
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Figure 7 illustrates mean histograms of differences (distances expressed in millimeters) between corresponding scans of the same subject for the full-face region as well as for
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each of the seven face regions, separately. The curves display normal distributions except the one representing the neck region. Table 3 summarizes the characteristics of the histograms of experiment B and shows that the mean and SD for the full-face region are −0.2 mm and 0.1 mm, respectively. All seven face regions except the neck region
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showed mean values close to zero. SD values range from 0.3 in the eyes to 0.6 mm in the chin region and more than 2 mm in the neck region. In Figure 8, the atlas face is color-coded in terms of (1) the mean of the absolute values of distances, (2) the SD of
DISCUSSION
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the distances, and (3) the maximum distance in each surface point.
Experiment A showed the SLS-2 scanner to be highly accurate, as it showed negligible systematic error. A random error of approximately 0.1 mm, as represented by the standard deviation (Table 2, Figure 5) for the full-face region, is considered fully acceptable in any practical clinical situation. Thus, on average, the SLS-2 scanner measured true dimensions of the mannequin model face geometry with an error well
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ACCEPTED MANUSCRIPT below 1 mm, as reported previously in similar settings and with a scanner setup (Weinberg, Naidoo et al., 2006). In flat areas such as the forehead, cheeks, chin and neck, it may be noted that the SD is less than 0.1 mm. The SD increases to
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approximately 0.2 mm in areas with more detailed structure and higher curvature such as the mouth, eyes, and nose. This may result from the fact that occlusion or shadowing is more likely to occur in these regions. Maximum values were higher, reaching almost
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4 mm (Table 2). Judging by the histograms, such outliers are few and typically the
result of the very sharp facial features of the mannequin obscuring a few locations from
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the camera, something that is not likely to happen with live faces (Figure 6). It should be noted that four small markers as well as eyelashes were glued to the surface of the mannequin, and these proved problematic for the scanner (Figure 6). However, by masking out the corresponding regions from the surface, these were removed from
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histograms and the statistical analysis. It may also be noted that the SLS-2, as used in the current setup with a fusion of three acquisitions, has a smaller but adequate field of view compared with the 3dMD. The blue arrow in Figure 6 marks this border.
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Also it may be noted that the semi-automatic fusion of the SLS-2 scans in the “Shape Fusion” software may introduce some degree of imprecision of the individual face
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reproductions. However, this is most likely negligible, due the high precision found in Experiment A.
Experiment B tested the SLS-2 in settings similar to clinical reality. In particular, the protocol was designed with longitudinal use in mind, reproducing accurate 3D images of live subjects in which the facial dimensions might change, for example, due to growth or treatment between consecutive scanning sessions.
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ACCEPTED MANUSCRIPT In experiment B, the study subjects were scanned the same day. Consequently, any measured difference would be due to either a limited reproducibility of the system itself, as quantified by experiment A, or a change in facial expression or head posture. A
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comparison of the histograms in Figure 7 to those in Figure 5 shows that a considerable amount of change has taken place that otherwise could not be attributed to the limited
systemic error of the SLS-2 itself. Table 3 shows that the variability (the SD values) is
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lowest by approximately 0.3 mm in the upper regions of the face, as expected, as the
areas of the eyes, forehead and nose are less influenced by changing facial expression.
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The largest SD values of approximately 0.6 mm occurred, as expected, in the lower parts of the face. Similarly, the areas of the mouth, cheek and chin are typically highly influenced by changing facial expression.
The large variability seen in the neck region may be understood from Figure 9. Here,
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the difference between the two scans of the same subject is demonstrated by superimposing the two scans in a lateral view. It becomes clear that the large variability in the neck region is due to variation in head posture.
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Standard deviations estimated in studies A and B are compared in Figure 10. It is evident that, rather than being the system error, the limiting factors in achieving
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reproducible results in live subjects are changes in facial expression between consecutive scans, and effects due to changes in head posture. It is important that this information be taken into consideration during protocol design and when interpreting data derived from the neck area using the SLS-2 with the present protocol. In situations in which the submandibular and neck regions are of no importance, the SD value falls below 0.5 mm. This is demonstrated by the rightmost bar in Figure 10, where the value has been carried on the full-face region minus the neck region.
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CONCLUSION This study finds that the SLS-2 scanner can be used for scanning of the adult human
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face in situations in which it is of importance to accurately quantify long-term changes in facial features over time, for example because of growth or surgery. It has been
demonstrated that the SLS-2 scanner is sufficiently accurate and that the limiting factor
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in the quantification of change is not the system error itself but, rather, errors due to changing facial expression and head posture. It is therefore recommended that a
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protocol for facial surface acquisition include the following elements:
Careful instructions to subjects in order to reproduce the same neutral expression during each scan
Standardized procedure for head posture
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Optimization of scanner angulation to avoid occlusion/shadows
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Avoidance of hair in the forehead region to retain sufficient forehead area for
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•
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alignment of surfaces over time
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ACCEPTED MANUSCRIPT Acknowledgements We would like to acknowledge the kind help and dedication from Jette Secher and Andrew Bell for the linguistic review and Dannie Korsgaard for consultancy regarding
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selection of test scanner and protocol.
Conflict of interest
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The authors reports no financial interests or potential conflicts of interest in regard to
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this work.
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Figure 1. SLS-2 scanner (Source: http://3dtool.ru/wp-
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content/uploads/2015/03/sls15_3.jpg).
Figure 2. Mannequin model in Experiment A in the 3dMDtrio scanner setup.
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Figure 3. Mannequin. (a) Photograph of the mannequin head. (b) Mean mannequin face in standard orientation. (c) Mannequin face with face regions numbered 1 to 7 (1 =
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neck; 2 = chin; 3 = mouth; 4 = nose; 5 = eyes; 6 = forehead; 7 = cheek). White coloration indicates parts of the face that were not included in any of the regions. (d) Same as in c but in a lateral view.
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Figure 4. Correct head position of live subject in Experiment B according to the three angles of image acquisition of the SLS-2. When seen through the camera feed on the PC monitor, the subject’s head should be centered vertically in the frontal plane according
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to the midline of the face and tilted backward such that a horizontal line intersects the
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lower border of the alar crease (a) and the intertragic notch (b).
Figure 5. Experiment A. Histograms of differences showing the distances between the reference face and each of the 30 scans acquired with the SLS-2.
Figure 6. Experiment A. The reference face color-coded according to (a) mean absolute values of distances, (b) SD values and (c) maximum mean error. Positive sign, shown as the red part of the color table, indicates that the SLS-2 scan is, on average, outside of
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ACCEPTED MANUSCRIPT the reference face. Negative sign, shown as the blue part of the color table, indicates that the SLS-2 scan is, on average, inside of the reference face. White coloration indicates errors very close to zero. White arrows indicate locations of structures not
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usually present in human faces (metal markers and large plastic eyelashes), representing areas not included in the results presented in Table 2 and Figure 5. Black arrows point to locations of occlusion/shadowing. Blue arrow points to the border of the field of view
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of the SLS-2 system.
surfaces of the same subject.
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Figure 7. Experiment B. Histograms of differences in distances between pairs of
Figure 8. Experiment B. Mean errors, left column, color-coded on the atlas surface.
respectively.
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Standard deviation and maximum value are shown in the middle and right columns,
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Figure 9. Experiment B. Left: Surface of example subject color-coded according to the absolute value of distances between two acquisitions. Right: Surfaces of the two
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acquisitions shown on top of each other using transparent blue and brown surface color, respectively.
Figure 10. Comparison of errors (represented by the standard deviation; Tables 2 and 3) from the two studies: Experiment A: quantifying accuracy and precision using a static mannequin face; Experiment B: quantifying precision using live subjects.
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Table 1. Comparison of specifications of the test and 3dMD scanners 3dMDtriotm scanner
Image acquisition time*
~8 s
~1.5 ms
Subject facial capture
90° 1 sensor
Resolution (depending on mode) Image capture technology
<0.06 mm Structured light scanning No
Validation for medical use Facial image rendering speed** Cost
6 sensors <0.2 mm
3D stererphotogrammetry
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Compatible with CT/CBCT
200°
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Configuration
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DAVID-SLS-2tm scanner
Yes
No
Yes
>5 min
9s
~$3000 $
$20-50.000
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SLS, structured light scanning; CT, computed tomography; CBCT, cone beam computed tomography. *Based on medium quality setting in the DAVID software. **Necessitates semi-manual fusion of three separate scans in the “Shapefusion” software package. Based
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on the first author’s experience level after 1 year of working with the system.
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3.
4.
5.
6.
7.
Neck
Chin
Mouth
Nose
Eyes
Forehead
Cheek
Face
Mean (mm)
0.0701
-0.0414
-0.0585
-0.0514
0.0745
0.0219
0.0392
0.00183
SD (mm)
0.0930
0.0573
0.117
0.238
0.271
0.0717
0.0801
0.0989
Max (mm)
2.295
0.256
0.910
3.681
3.804
0.979
3.683
3.683
% > 0.5 mm
0.025
0.000
0.57
2.76
4.26
0.092
0.16
0.18
% > 1.0 mm
0.011
0.000
0.000
0.94
1.42
0.000
0.031
0.040
95% cutoff (mm)
0.22
0.14
0.28
0.36
0.45
0.15
0.17
0.19
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SD, standard deviation; Max, maximum.
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1.
Errors represent values obtained in the region indicated. The rightmost column provides values for the
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full-face region (union of regions 1-7).
ACCEPTED MANUSCRIPT Table 3. Results of Experiment B 1.
2.
3.
4.
5.
6.
7.
Neck
Chin
Mouth
Nose
Eyes
Forehead
Cheek
Mean (mm)
-1.600
-0.150
-0.160
0.0100
0.0300
-0.0373
-0.108
-0.240
SD (mm)
2.124
0.600
0.536
0.340
0.299
0.328
0.592
0.955
Max (mm)
11.377
1.931
2.300
5.807
3.467
4.669
7.728
11.377
% > 1 mm
61.73
11.08
9.67
2.67
0.88
1.84
6.38
10.7
% > 2 mm
33.27
0.000
0.010
0.26
0.080
0.35
1.26
3.9
95% cutoff (mm)
5.71
1.21
1.17
0.82
0.60
0.63
1.00
1.65
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Errors represent values obtained in the region indicated.
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SD, standard deviation; Max, maximum.
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Face
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Figure 10.
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Standard Deviation in mm
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Figure 9.
S1010-5182(17)30244-5
DOI:
10.1016/j.jcms.2017.07.006
Reference:
YJCMS 2729
To appear in:
Journal of Cranio-Maxillo-Facial Surgery
Received Date: 13 April 2017 Revised Date:
15 June 2017
Accepted Date: 18 July 2017
Please cite this article as: Secher JJ, Darvann TA, Pinholt EM, Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging, Journal of Cranio-Maxillofacial Surgery (2017), doi: 10.1016/j.jcms.2017.07.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Accuracy and reproducibility of the DAVID SLS-2 scanner in three-dimensional facial imaging
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Jesper Jared Secher1,2, DDS, PhD-student Tron Andre Darvann3, MSc, PhD, Research Engineer
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Else Marie Pinholt1, 2, DDS, Professor, Consultant, MSci, Dr Odont.
1: Department of Oral and Maxillofacial Surgery, Hospital of South West Denmark,
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Finsensgade 35, DK - 6700 Esbjerg, Denmark.
2: University of Southern Denmark, Faculty of Health, Institute for Regional Services Sciences, Winsløwparken 19, 3. 5000 Odense C, Denmark.
3: University of Copenhagen, Department of Odontology, 3D Craniofacial Image
Corresponding author
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Dr. Jesper Jared Secher
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Research Laboratory, 20, Nørre Allé, DK-2200 Copenhagen N, Denmark.
Department of Oral and Maxillofacial Surgery
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Hospital of South West Denmark, Finsensgade 35, DK - 6700 Esbjerg, Denmark Telephone: (+45) 40269517 E-mail address: [email protected]
ACCEPTED MANUSCRIPT Summary
Purpose: A prospective study was performed to test the accuracy and reproducibility of
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the DAVID-SLS-2 scanner (SLS-2) [DAVID Vision Systems GmbH], compared to the validated 3dMDtrio scanner (3dMD) [3dMD, LLC, Atlanta, GA, USA].
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Materials and Methods: The accuracy of the SLS-2 was determined through multiple scans of a mannequin face model using both scanners. The reproducibility of a protocol
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for achieving consistent three-dimensional (3D) face scans in live subjects was carried out using the SLS-2. A precision of <1 mm was considered clinically significant.
Results: The mannequin face model was reproduced with no significant errors in the
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SLS-2 compared to the 3dMDtrio, with normally distributed data (mean = 0.002 mm; SD = 0.01 mm). In live subjects, the forehead, midface, chin and general face region showed mean errors and SD < 0.24 mm and < 1 mm, respectively. In the neck area, the
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data were not found to be normally distributed (mean = −1.6 mm; SD = 2.1 mm).
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Conclusion: Structured light scanning may be used for acquiring 3D face scans in live subjects in a radiation-free and reproducible manner, provided that the head of the subject is positioned in the same posture for each scan. Special care is recommended in positioning the head in the sagittal plane during scanning.
Keywords: structured light scanning, 3D photogrammetry, accuracy, reproducibility
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ACCEPTED MANUSCRIPT INTRODUCTION The use of three-dimensional (3D) images to reproduce facial surfaces in cranio- and maxillofacial surgery has been shown to be a valuable perioperative tool (Rana, Gellrich
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et al., 2011; Meulstee, Liebregts et al., 2015; Ostwald, Berssenbrugge et al., 2015). A high level of accuracy and reproducibility in 3D imaging is crucial for clinical and research purposes. Reportedly, a mean error < 1 mm is considered to be clinically
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significant (Maal, van Loon et al., 2010; Hammoudeh, Howell et al., 2015; Nord, Ferjencik et al., 2015; Zinser and Zoeller, 2015; Ye, Lv et al., 2016).
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Sources of 3D surface imaging are represented primarily by the non-ionizing modalities of laser scanning, structured light scanning (SLS) and 3D stereophotogrammetry. Structured light scanners emit light within visible wavelengths as opposed to laser light of the classic laser scanner. Previously, SLS systems have been classified as laser type
advances.
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scanners, but have emerged as a scanning modality of their own due to recent technical
Three-dimensional stereophotogrammetry uses simultaneous multi-angle photography
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to create a 3D model, and is currently considered the gold standard in facial surface imaging due to fast image acquisition times in combination with a high level of
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reliability and precision (Wong, Oh et al., 2008; Maal, van Loon et al., 2010; Nord, Ferjencik et al., 2015; Hermann, Darvann et al., 2016). Three-dimensional stereophotogrammetry is considerably more expensive compared to laser scanning and SLS, but is less prone to motion artifacts due to image acquisition times measured in milliseconds in contrast to seconds in laser scanning and SLS. The latter may also require multiple scans from various angles, as a single sensor is common in these systems, in contrast to a single image acquisition in 3D stereophotogrammetry.
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ACCEPTED MANUSCRIPT Despite the obvious advantages of 3D photogrammetry, new SLS scanners are frequently being developed, and the quality gap between the two imaging modalities is closing, as shown in recent studies (Kim, Jung et al., 2015; Modabber, Peters et al.,
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2016; Ye, Lv et al, 2016; Rodriguez-Florez, Goktekin et al., 2017). In combination with a considerably lower price compared to 3D stereo-photogrammetry, SLS may offer an
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alternative from a cost-effectiveness point of view.
The aim of this study was to determine the following: (1) the accuracy and
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reproducibility of a modern SLS scanner compared to an established 3D photogrammetric system in a mannequin face model; and (2) the reproducibility of a scanning protocol designed for scanning live human faces over time using the SLS
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scanner.
MATERIALS AND METHODS
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Subjects and scanners
Two experiments, A and B, were performed. In experiment A, the face of a mannequin
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torso was scanned. The mannequin head contained four face markers and eyelashes irrelevant to this study, and were therefore digitally masked out prior to image measurement. Experiment B included 10 healthy human study subjects, eight female and two male, who signed a consent form prior to participation in the study. The scanner to be tested was the DAVID-SLS-2, DAVID Vision Systems GmbH (SLS2). In experiment A, the results of the SLS-2 were compared to the results of the 3dMDtrio system, 3dMD, Atlanta, GA, USA (3dMD).
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ACCEPTED MANUSCRIPT Important practical differences between the two systems consist of image acquisition time and the cost of the scanners. The SLS-2 requires three scans to cover the full-face region from ear to ear, with 4-10 seconds per image, compared to 1.5 milliseconds for a
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single scan in the 3dMD. The test scanner SLS-2 is priced at around $3000, compared to the 3dMD at $20,000-50,000. Further technical specifications are listed in Table 1.
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Ethics considerations
The principles of the Declaration of Helsinki were observed throughout the experiment.
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The study was granted exemption by the local institutional review board. Written informed consent was obtained from the study participants according to local ethical and data management regulations.
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Experiment A
The accuracy of the SLS-2 (Figure 1) was determined by 30 consecutive scans of the mannequin face. In order to obtain similar coverage of the face from ear to ear as in the
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3dMD scanner (Figure 2), the mannequin was repositioned three times in between the acquisitions in the SLS-2 (Figure 3a). Immediately after image acquisition, the three
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scans were fused together using the accompanying software “Shape Fusion” (DAVID 3D Solutions GbR, Braunschweig, Germany). An average processing time of 5-10 minutes was required to complete a full-surface reconstruction of the face using the default settings in “Shape Fusion.” The process was semi-automatic and involved manual input in terms of selecting the scans and the order in which to fuse them into one model.
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ACCEPTED MANUSCRIPT A reference face (Figure 3b) was constructed by averaging 30 3dMD scans taken of the mannequin on the same day. The mannequin was repositioned before each acquisition for all 30 acquisitions. An iterated closest point (ICP) algorithm was used in order to
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bring the 30 scans into best alignment before averaging. Before a meaningful averaging could be carried out, detailed point correspondence had to be established among all 30 scans. The following standard algorithm was used: (1) Pick a reference scan at random
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among the 30 aligned scans. (2) For each surface point on the reference scan, determine the closest location on the 29 other scans; use these as anatomically corresponding
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locations across all scans. (3) Calculate pointwise arithmetic mean to form a new reference face. (4) In order to minimize bias towards the shape of the originally chosen reference scan, repeat the above procedure (steps 2 and 3) using the new reference shape. The reference face was subsequently segmented into seven regions comprising
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the forehead, eyes, nose, mouth, cheek, chin and neck (Figure 3c-d) by fitting a presegmented standard face atlas to the reference face by non-rigid surface registration (Szeliski and Lavallee, 1994; Rueckert, Sonoda et al., 1999; Rueckert, Frangi et al.,
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2003).
Each of the 30 SLS-2 face scans was in turn compared to the reference face by
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calculating, at every surface point of the SLS-2 surface, the distance to the closest location on the reference face after achieving optimal overall spatial alignment between the two using the Iterated Closest Point algorithm (ICP) (Zhang, 1994). The ICP algorithm resulted in 30 distance maps that was color-coded onto the reference face for visual inspection of the spatial distribution of distances for each of the 30 scans. The distance was given a sign depending on whether the SLS-2 scan was inside (negative) or outside (positive) of the reference face. Histograms of distances were calculated for
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ACCEPTED MANUSCRIPT each of the seven face regions as well as for the full-face region, the latter consisting of the union of the seven regions. Mean histograms were also calculated, representing the distribution of differences in all 30 distance maps. The mean of the distribution was
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used as a measure of systematic error. A mean different from zero would reveal that the SLS-2 scanner under- or overestimated true dimensions. The standard deviation (SD) of the distribution provided another measure of the error of the SLS-2. The maximum
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difference was calculated, as well as the difference where 95% of surface points were
included. Finally, entities pertaining to the cumulative histogram were calculated as the
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percentage of points with a difference larger than a given limit. Two limits were chosen and tabulated: 0.5 mm and 1.0 mm respectively. To calculate and display a distance map representing the mean of all 30 distance maps, it was necessary to establish a detailed point correspondence between all surfaces. This was achieved by fitting a face
1994).
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Experiment B
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atlas to all surfaces by use of non-rigid surface registration (Szeliski and Lavallee,
Ten live subjects were scanned twice consecutively in the SLS-2. The subjects were
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seated with their heads on a headrest, slightly tilted back and with their teeth in maximal intercuspidal position (Figure 4). The head posture was aligned according the vertical midline of the face, and the degree of the head tilt was secured by positioning the head of the study subject so that a horizontal line intersected the lateral corner of the nose and the intertragic notch in either side. This was done to avoid blank areas due to the single sensor of the SLS-2 and was guided by the horizontal grid lines of the scanner window on the personal computer (PC) monitor.
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ACCEPTED MANUSCRIPT Three SLS-2 scans were needed for a full face scan consisting of a frontal scan perpendicular to the midline of the face and bilateral scans spaced approximately 45-55° measured from the facial midline (Figure 4).
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Time was provided for subjects to walk and talk between the two sessions, simulating two independent visits to the photographer. Before each of the two acquisitions, the chair and headrest were readjusted and the subject was instructed to keep a relaxed,
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neutral expression during the scan.
Spatial differences were quantified in each surface point as the closest distance between
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the two acquired surfaces after the two surfaces had been brought into an optimal spatial alignment using ICP on a subregion of the face comprising the lower part of the forehead and the upper part of the bridge of the nose. This subregion was chosen because it could be assumed to be largely unaffected by variation in facial expression.
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The distance values were color-coded onto one of the surfaces for inspection of spatial distribution. Histograms of distances were calculated for each subject and each of the seven face regions, as well as for the full-face region. Mean histograms for all subjects
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and regions were calculated in a similar way as for experiment A. As for experiment A, a mean, SD, maximum 95% cutoff and percentage of points with
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distances larger than given limits were calculated. To investigate the spatial distribution of mean differences in the whole population of subjects, it was necessary to establish a detailed point correspondence between individual distance maps. This was achieved by deforming a face atlas to each subject face using an automatic method (Szeliski and Lavallee 1994, Rueckert, Sonoda et al. 1999, Rueckert, Frangi et al. 2003) initialized by four manually placed landmarks on (1) the right and (2) the left ear at the junction between the tragus and the crus of the helix, (3) the sellion, and (4) the pronasale. The
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ACCEPTED MANUSCRIPT face atlas contained the seven face regions shown in Figure 3c-d, and these were transferred to each of the subjects by the deformation.
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Data handling Surface registration and visualization of results in terms of color-coded surfaces were performed in the software package “Landmarker” developed in-house based on VTK
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(William Scroeder 1996, Tron Andre Darvann 2008). Descriptive statistics and
histogram calculations were performed in IDL (Interactive Data Language, Research
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Systems Inc., Boulder, CO, USA). Atlas deformation was performed in the Image Registration Tool Kit (IRTK) software developed by Daniel Rueckert, Imperial College
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London, UK, under a license to Ixico Ltd.
RESULTS
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Experiment A
Figure 5 shows mean histograms of differences (distances expressed in millimeters)
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among all 30 mannequin face scans and the reference face for the full-face region as well as for each of the seven face regions separately. All histograms are reasonably normally distributed, with mean values close to zero and with varying but small standard deviations, as reflected in Table 2. The SD is 0.1 mm for the whole face, whereas it varies between 0.07 mm (forehead) and 0.27 mm (eye region) for the seven face regions. Figure 6 provides a display of the magnitude and spatial distribution of the distances with the reference surface shown as color-coded in terms of (1) the mean of
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ACCEPTED MANUSCRIPT the absolute values of distances, (2) the SD of the distances, and (3) the maximum distance in each surface point. The spatial coverage of the SLS-2 scanner is demonstrated to be smaller than the 3dMD but still covering the full-face region,
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including the ears.
Experiment B
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Figure 7 illustrates mean histograms of differences (distances expressed in millimeters) between corresponding scans of the same subject for the full-face region as well as for
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each of the seven face regions, separately. The curves display normal distributions except the one representing the neck region. Table 3 summarizes the characteristics of the histograms of experiment B and shows that the mean and SD for the full-face region are −0.2 mm and 0.1 mm, respectively. All seven face regions except the neck region
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showed mean values close to zero. SD values range from 0.3 in the eyes to 0.6 mm in the chin region and more than 2 mm in the neck region. In Figure 8, the atlas face is color-coded in terms of (1) the mean of the absolute values of distances, (2) the SD of
DISCUSSION
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the distances, and (3) the maximum distance in each surface point.
Experiment A showed the SLS-2 scanner to be highly accurate, as it showed negligible systematic error. A random error of approximately 0.1 mm, as represented by the standard deviation (Table 2, Figure 5) for the full-face region, is considered fully acceptable in any practical clinical situation. Thus, on average, the SLS-2 scanner measured true dimensions of the mannequin model face geometry with an error well
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ACCEPTED MANUSCRIPT below 1 mm, as reported previously in similar settings and with a scanner setup (Weinberg, Naidoo et al., 2006). In flat areas such as the forehead, cheeks, chin and neck, it may be noted that the SD is less than 0.1 mm. The SD increases to
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approximately 0.2 mm in areas with more detailed structure and higher curvature such as the mouth, eyes, and nose. This may result from the fact that occlusion or shadowing is more likely to occur in these regions. Maximum values were higher, reaching almost
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4 mm (Table 2). Judging by the histograms, such outliers are few and typically the
result of the very sharp facial features of the mannequin obscuring a few locations from
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the camera, something that is not likely to happen with live faces (Figure 6). It should be noted that four small markers as well as eyelashes were glued to the surface of the mannequin, and these proved problematic for the scanner (Figure 6). However, by masking out the corresponding regions from the surface, these were removed from
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histograms and the statistical analysis. It may also be noted that the SLS-2, as used in the current setup with a fusion of three acquisitions, has a smaller but adequate field of view compared with the 3dMD. The blue arrow in Figure 6 marks this border.
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Also it may be noted that the semi-automatic fusion of the SLS-2 scans in the “Shape Fusion” software may introduce some degree of imprecision of the individual face
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reproductions. However, this is most likely negligible, due the high precision found in Experiment A.
Experiment B tested the SLS-2 in settings similar to clinical reality. In particular, the protocol was designed with longitudinal use in mind, reproducing accurate 3D images of live subjects in which the facial dimensions might change, for example, due to growth or treatment between consecutive scanning sessions.
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ACCEPTED MANUSCRIPT In experiment B, the study subjects were scanned the same day. Consequently, any measured difference would be due to either a limited reproducibility of the system itself, as quantified by experiment A, or a change in facial expression or head posture. A
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comparison of the histograms in Figure 7 to those in Figure 5 shows that a considerable amount of change has taken place that otherwise could not be attributed to the limited
systemic error of the SLS-2 itself. Table 3 shows that the variability (the SD values) is
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lowest by approximately 0.3 mm in the upper regions of the face, as expected, as the
areas of the eyes, forehead and nose are less influenced by changing facial expression.
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The largest SD values of approximately 0.6 mm occurred, as expected, in the lower parts of the face. Similarly, the areas of the mouth, cheek and chin are typically highly influenced by changing facial expression.
The large variability seen in the neck region may be understood from Figure 9. Here,
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the difference between the two scans of the same subject is demonstrated by superimposing the two scans in a lateral view. It becomes clear that the large variability in the neck region is due to variation in head posture.
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Standard deviations estimated in studies A and B are compared in Figure 10. It is evident that, rather than being the system error, the limiting factors in achieving
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reproducible results in live subjects are changes in facial expression between consecutive scans, and effects due to changes in head posture. It is important that this information be taken into consideration during protocol design and when interpreting data derived from the neck area using the SLS-2 with the present protocol. In situations in which the submandibular and neck regions are of no importance, the SD value falls below 0.5 mm. This is demonstrated by the rightmost bar in Figure 10, where the value has been carried on the full-face region minus the neck region.
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CONCLUSION This study finds that the SLS-2 scanner can be used for scanning of the adult human
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face in situations in which it is of importance to accurately quantify long-term changes in facial features over time, for example because of growth or surgery. It has been
demonstrated that the SLS-2 scanner is sufficiently accurate and that the limiting factor
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in the quantification of change is not the system error itself but, rather, errors due to changing facial expression and head posture. It is therefore recommended that a
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protocol for facial surface acquisition include the following elements:
Careful instructions to subjects in order to reproduce the same neutral expression during each scan
Standardized procedure for head posture
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Optimization of scanner angulation to avoid occlusion/shadows
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Avoidance of hair in the forehead region to retain sufficient forehead area for
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alignment of surfaces over time
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ACCEPTED MANUSCRIPT Acknowledgements We would like to acknowledge the kind help and dedication from Jette Secher and Andrew Bell for the linguistic review and Dannie Korsgaard for consultancy regarding
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selection of test scanner and protocol.
Conflict of interest
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The authors reports no financial interests or potential conflicts of interest in regard to
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this work.
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Zhang, Z: Iterative point matching for registration of free-form curves and surfaces. Int J Computer Vision 13(2): 119-152, 1994
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Zinser, M. and J. Zoeller: Computer-Designed Splints for Surgical Transfer of 3D Orthognathic Planning. Facial Plast Surg 31(5): 474-490, 2015
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Figure 1. SLS-2 scanner (Source: http://3dtool.ru/wp-
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content/uploads/2015/03/sls15_3.jpg).
Figure 2. Mannequin model in Experiment A in the 3dMDtrio scanner setup.
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Figure 3. Mannequin. (a) Photograph of the mannequin head. (b) Mean mannequin face in standard orientation. (c) Mannequin face with face regions numbered 1 to 7 (1 =
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neck; 2 = chin; 3 = mouth; 4 = nose; 5 = eyes; 6 = forehead; 7 = cheek). White coloration indicates parts of the face that were not included in any of the regions. (d) Same as in c but in a lateral view.
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Figure 4. Correct head position of live subject in Experiment B according to the three angles of image acquisition of the SLS-2. When seen through the camera feed on the PC monitor, the subject’s head should be centered vertically in the frontal plane according
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to the midline of the face and tilted backward such that a horizontal line intersects the
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lower border of the alar crease (a) and the intertragic notch (b).
Figure 5. Experiment A. Histograms of differences showing the distances between the reference face and each of the 30 scans acquired with the SLS-2.
Figure 6. Experiment A. The reference face color-coded according to (a) mean absolute values of distances, (b) SD values and (c) maximum mean error. Positive sign, shown as the red part of the color table, indicates that the SLS-2 scan is, on average, outside of
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usually present in human faces (metal markers and large plastic eyelashes), representing areas not included in the results presented in Table 2 and Figure 5. Black arrows point to locations of occlusion/shadowing. Blue arrow points to the border of the field of view
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of the SLS-2 system.
surfaces of the same subject.
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Figure 7. Experiment B. Histograms of differences in distances between pairs of
Figure 8. Experiment B. Mean errors, left column, color-coded on the atlas surface.
respectively.
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Standard deviation and maximum value are shown in the middle and right columns,
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Figure 9. Experiment B. Left: Surface of example subject color-coded according to the absolute value of distances between two acquisitions. Right: Surfaces of the two
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acquisitions shown on top of each other using transparent blue and brown surface color, respectively.
Figure 10. Comparison of errors (represented by the standard deviation; Tables 2 and 3) from the two studies: Experiment A: quantifying accuracy and precision using a static mannequin face; Experiment B: quantifying precision using live subjects.
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Table 1. Comparison of specifications of the test and 3dMD scanners 3dMDtriotm scanner
Image acquisition time*
~8 s
~1.5 ms
Subject facial capture
90° 1 sensor
Resolution (depending on mode) Image capture technology
<0.06 mm Structured light scanning No
Validation for medical use Facial image rendering speed** Cost
6 sensors <0.2 mm
3D stererphotogrammetry
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Compatible with CT/CBCT
200°
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Configuration
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DAVID-SLS-2tm scanner
Yes
No
Yes
>5 min
9s
~$3000 $
$20-50.000
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SLS, structured light scanning; CT, computed tomography; CBCT, cone beam computed tomography. *Based on medium quality setting in the DAVID software. **Necessitates semi-manual fusion of three separate scans in the “Shapefusion” software package. Based
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on the first author’s experience level after 1 year of working with the system.
ACCEPTED MANUSCRIPT Table 2. Results of Experiment A 2.
3.
4.
5.
6.
7.
Neck
Chin
Mouth
Nose
Eyes
Forehead
Cheek
Face
Mean (mm)
0.0701
-0.0414
-0.0585
-0.0514
0.0745
0.0219
0.0392
0.00183
SD (mm)
0.0930
0.0573
0.117
0.238
0.271
0.0717
0.0801
0.0989
Max (mm)
2.295
0.256
0.910
3.681
3.804
0.979
3.683
3.683
% > 0.5 mm
0.025
0.000
0.57
2.76
4.26
0.092
0.16
0.18
% > 1.0 mm
0.011
0.000
0.000
0.94
1.42
0.000
0.031
0.040
95% cutoff (mm)
0.22
0.14
0.28
0.36
0.45
0.15
0.17
0.19
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SD, standard deviation; Max, maximum.
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1.
Errors represent values obtained in the region indicated. The rightmost column provides values for the
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full-face region (union of regions 1-7).
ACCEPTED MANUSCRIPT Table 3. Results of Experiment B 1.
2.
3.
4.
5.
6.
7.
Neck
Chin
Mouth
Nose
Eyes
Forehead
Cheek
Mean (mm)
-1.600
-0.150
-0.160
0.0100
0.0300
-0.0373
-0.108
-0.240
SD (mm)
2.124
0.600
0.536
0.340
0.299
0.328
0.592
0.955
Max (mm)
11.377
1.931
2.300
5.807
3.467
4.669
7.728
11.377
% > 1 mm
61.73
11.08
9.67
2.67
0.88
1.84
6.38
10.7
% > 2 mm
33.27
0.000
0.010
0.26
0.080
0.35
1.26
3.9
95% cutoff (mm)
5.71
1.21
1.17
0.82
0.60
0.63
1.00
1.65
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Errors represent values obtained in the region indicated.
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SD, standard deviation; Max, maximum.
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Face
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Standard Deviation in mm
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Figure 6.
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Figure 8.
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Figure 9.