Growth patterns and shape development of the paediatric mandible – A 3D statistical model
AbstractBackground/aimTo develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. MethodsComputed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47...
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| Published in: | Bone Reports Vol. 16; p. 101528 |
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| Abstract | AbstractBackground/aimTo develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. MethodsComputed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements. ResultsA 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = −0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population. ConclusionThe presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up. |
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| AbstractList | AbstractBackground/aimTo develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. MethodsComputed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements. ResultsA 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = −0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population. ConclusionThe presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up. • Shape and development patterns of the paediatric mandible (0 – 4 years) were evaluated using a dataset of 242 CT scans. • A 3D morphable model of the paediatric mandible was constructed using principal component analysis (PCA). • Validation experiments demonstrated that the 3D morphable model can produce realistic novel mandible samples. • Partial least squares (PLS) regression was applied to the dataset to evaluate shape differences for age and sex. • The first shape model correlated strongly with age for PCA and PLS, though little correlation was seen between shape and sex. To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.Background/aimTo develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements.MethodsComputed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements.A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = -0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population.ResultsA 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = -0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population.The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up.ConclusionThe presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up. To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements. A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = -0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population. The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up. Background/aim: To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. Methods: Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements. Results: A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = −0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population. Conclusion: The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up. To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements. A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = −0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population. The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up. •Shape and development patterns of the paediatric mandible (0 – 4 years) were evaluated using a dataset of 242 CT scans.•A 3D morphable model of the paediatric mandible was constructed using principal component analysis (PCA).•Validation experiments demonstrated that the 3D morphable model can produce realistic novel mandible samples.•Partial least squares (PLS) regression was applied to the dataset to evaluate shape differences for age and sex.•The first shape model correlated strongly with age for PCA and PLS, though little correlation was seen between shape and sex. |
| ArticleNumber | 101528 |
| Author | El Ghoul, Khalid Koudstaal, Maarten J Khonsari, Roman H Schievano, Silvia van de Lande, Lara S Zafeiriou, Stefanos Dunaway, David J O' Sullivan, Eimear |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35399871$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1007/s11263-017-1009-7 10.1016/j.archoralbio.2017.01.018 10.1016/S1361-8415(03)00034-3 10.1097/01.PRS.0000169940.69315.9C 10.1097/GOX.0000000000000582 10.2319/020309-67.1 10.1111/j.1469-7580.2005.00479.x 10.14219/jada.archive.1941.0157 10.1038/s41598-019-49506-1 10.1007/s00330-010-1828-1 10.1002/ajpa.23933 10.1111/j.1556-4029.2006.00311.x 10.1109/TPAMI.2020.2991150 10.1007/s12024-007-9015-7 10.1016/j.bone.2020.115600 10.1111/joa.12008 10.1038/s41598-021-98421-x |
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| Keywords | Paediatric mandible 3D morphable model Morphometrics Partial least squares Infant mandible Statistical model |
| Language | English |
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| References | Karlo, Stolzmann, Habernig, Müller, Saurenmann, Kellenberger (bb0070) 2010; 20 Li, Park, Liu, Zhang, Reed, Rupp, Hoff, Hu (bb0100) 2015; 10 Morice, Cornette, Giudice, Collet, Paternoster, Arnaud, Galliani, Picard, Legeai-Mallet, Khonsari (bb0110) 2020; 141 Franklin, Oxnard, O'Higgins, Dadour (bb0045) 2007; 52 Ploumpis, Ververas, O’Sullivan, Moschoglou, Wang, Pears, Smith, Gecer, Zafeiriou (bb0120) 2020; 43 Zolfaghari, Epain, Jin, Glaunes, Tew (bb0155) 2016 Kelly, Vorperian, Wang, Tillman, Werner, Chung, Gentry (bb0075) 2017; 77 Hutchinson, L’Abbé, Oettle (bb0065) 2012; 217 Booth, Roussos, Ponniah, Dunaway, Zafeiriou (bb0020) 2018; 126 Remy, Godio-Raboutet, Captier, Burgart, Bonnaure, Thollon, Guyot (bb0125) 2019; 170 Franklin, Cardini, O’Higgins, Oxnard, Dadour (bb0050) 2008; 4 E O'Sullivan LS van de Lande A Papaioannou RW Breakey NO Jeelani A Ponniah C Duncan S Schievano RH Khonsari S Zafeiriou . Craniofacial Syndrome Identification Using Convolutional Mesh Autoencoders. Available at SSRN 3795325. Knoops, Papaioannou, Borghi, Breakey, Wilson, Jeelani, Zafeiriou, Steinbacher, Padwa, Dunaway (bb0090) 2019; 9 Schipper, van Lieshout, Böhringer, Padwa, Robben, van Rijn, Koudstaal, Lequin, Wolvius (bb0130) 2021 Vallabh, Zhang, Fernandez, Dimitroulis, Ackland (bb0150) 2020 Blanz, Vetter (bb0010) 1999 Amberg, Romdhani, Vetter (bb0005) 2007; Vols 1-8 Booth, Roussos, Zafeiriou, Ponniah, Dunaway (bb0015) 2016 Klop, Amsterdam (bb0085) 2021; 11 Swanson, Mitchell, Wink, Taylor, Bartlett (bb0145) 2016; 4 Dai, Pears, Smith (bb0040) 2018 Stunz (bb0140) 1941; 28 Hilger, Larsen, Wrobel (bb0060) 2003; 7 Gao, Chen, Li, Li, Liu, Wu, Hao, Wang (bb0055) 2020; 78 Liu, Behrents, Buschang (bb0105) 2010; 80 Smartt, Low, Bartlett (bb0135) 2005; 116 Krarup, Darvann, Larsen, Marsh, Kreiborg (bb0095) 2005; 207 Claire Kane, Lauren (bb0025) 2016; 1 Dai, Pears, Smith, Duncan (bb0035) 2017 Khamis, Taylor, Shotton, Keskin, Izadi, Fitzgibbon (bb0080) 2015 Coquerelle, Prados-Frutos, Benazzi, Bookstein, Senck, Mitteroecker, Weber (bb0030) 2013; 222 Booth (10.1016/j.bonr.2022.101528_bb0020) 2018; 126 Franklin (10.1016/j.bonr.2022.101528_bb0050) 2008; 4 Krarup (10.1016/j.bonr.2022.101528_bb0095) 2005; 207 10.1016/j.bonr.2022.101528_bb0115 Ploumpis (10.1016/j.bonr.2022.101528_bb0120) 2020; 43 Khamis (10.1016/j.bonr.2022.101528_bb0080) 2015 Coquerelle (10.1016/j.bonr.2022.101528_bb0030) 2013; 222 Klop (10.1016/j.bonr.2022.101528_bb0085) 2021; 11 Dai (10.1016/j.bonr.2022.101528_bb0040) 2018 Remy (10.1016/j.bonr.2022.101528_bb0125) 2019; 170 Morice (10.1016/j.bonr.2022.101528_bb0110) 2020; 141 Swanson (10.1016/j.bonr.2022.101528_bb0145) 2016; 4 Vallabh (10.1016/j.bonr.2022.101528_bb0150) 2020 Karlo (10.1016/j.bonr.2022.101528_bb0070) 2010; 20 Franklin (10.1016/j.bonr.2022.101528_bb0045) 2007; 52 Dai (10.1016/j.bonr.2022.101528_bb0035) 2017 Stunz (10.1016/j.bonr.2022.101528_bb0140) 1941; 28 Gao (10.1016/j.bonr.2022.101528_bb0055) 2020; 78 Li (10.1016/j.bonr.2022.101528_bb0100) 2015; 10 Zolfaghari (10.1016/j.bonr.2022.101528_bb0155) 2016 Hutchinson (10.1016/j.bonr.2022.101528_bb0065) 2012; 217 Booth (10.1016/j.bonr.2022.101528_bb0015) 2016 Schipper (10.1016/j.bonr.2022.101528_bb0130) 2021 Smartt (10.1016/j.bonr.2022.101528_bb0135) 2005; 116 Knoops (10.1016/j.bonr.2022.101528_bb0090) 2019; 9 Hilger (10.1016/j.bonr.2022.101528_bb0060) 2003; 7 Liu (10.1016/j.bonr.2022.101528_bb0105) 2010; 80 Amberg (10.1016/j.bonr.2022.101528_bb0005) 2007; Vols 1-8 Blanz (10.1016/j.bonr.2022.101528_bb0010) 1999 Claire Kane (10.1016/j.bonr.2022.101528_bb0025) 2016; 1 Kelly (10.1016/j.bonr.2022.101528_bb0075) 2017; 77 |
| References_xml | – volume: 170 start-page: 496 year: 2019 end-page: 506 ident: bb0125 article-title: Morphometric characterization of the very young child mandibular growth pattern: what happen before and after the deciduous dentition development? publication-title: Am. J. Phys. Anthropol. – volume: 11 start-page: 18843 year: 2021 ident: bb0085 article-title: A three-dimensional statistical shape model of the growing mandible publication-title: Sci. Rep. – volume: 28 start-page: 921 year: 1941 end-page: 928 ident: bb0140 article-title: The mandibular angle in infancy: its significance and modification publication-title: J. Am. Dent. Assoc. – reference: E O'Sullivan LS van de Lande A Papaioannou RW Breakey NO Jeelani A Ponniah C Duncan S Schievano RH Khonsari S Zafeiriou . Craniofacial Syndrome Identification Using Convolutional Mesh Autoencoders. Available at SSRN 3795325. – volume: 217 year: 2012 ident: bb0065 article-title: An assessment of early mandibular growth publication-title: Forensic Sci. Int. – volume: 7 start-page: 425 year: 2003 end-page: 433 ident: bb0060 article-title: Growth modeling of human mandibles using non-euclidean metrics publication-title: Med. Image Anal. – start-page: 1 year: 2021 end-page: 11 ident: bb0130 article-title: Modelling growth curves of the normal infant’s mandible: 3D measurements using computed tomography publication-title: Clin. Oral Investig. – volume: 52 start-page: 6 year: 2007 end-page: 10 ident: bb0045 article-title: Sexual dimorphism in the subadult mandible: quantification using geometric morphometrics publication-title: J. Forensic Sci. – volume: Vols 1-8 year: 2007 ident: bb0005 article-title: Optimal step nonrigid ICP algorithms for surface registration publication-title: 2007 Ieee Conference on Computer Vision and Pattern Recognition – volume: 116 start-page: 14e year: 2005 end-page: 23e ident: bb0135 article-title: The pediatric mandible: I. A primer on growth and development publication-title: Plast. Reconstr. Surg. – start-page: 3085 year: 2017 end-page: 3093 ident: bb0035 article-title: A 3d morphable model of craniofacial shape and texture variation publication-title: Proceedings of the IEEE International Conference on Computer Vision – start-page: 5543 year: 2016 end-page: 5552 ident: bb0015 article-title: A 3d morphable model learnt from 10,000 faces publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition – volume: 77 start-page: 27 year: 2017 end-page: 38 ident: bb0075 article-title: Characterizing mandibular growth using three-dimensional imaging techniques and anatomic landmarks publication-title: Arch. Oral Biol. – volume: 207 start-page: 669 year: 2005 end-page: 682 ident: bb0095 article-title: Three-dimensional analysis of mandibular growth and tooth eruption publication-title: J. Anat. – start-page: 1771 year: 2016 end-page: 1775 ident: bb0155 article-title: Generating a morphable model of ears publication-title: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) – volume: 78 year: 2020 ident: bb0055 article-title: A novel geometric morphometric analytical method for classifying mandibular morphology in infants with isolated Pierre Robin sequence publication-title: J. Oral Maxillofac. Surg. – volume: 9 start-page: 1 year: 2019 end-page: 12 ident: bb0090 article-title: A machine learning framework for automated diagnosis and computer-assisted planning in plastic and reconstructive surgery publication-title: Sci. Rep. – volume: 141 year: 2020 ident: bb0110 article-title: Early mandibular morphological differences in patients with FGFR2 and FGFR3-related syndromic craniosynostoses: a 3D comparative study publication-title: Bone – volume: 10 year: 2015 ident: bb0100 article-title: A statistical skull geometry model for children 0–3 years old publication-title: PLoS One – start-page: 187 year: 1999 end-page: 194 ident: bb0010 article-title: A morphable model for the synthesis of 3D faces publication-title: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques – volume: 43 start-page: 4142 year: 2020 end-page: 4160 ident: bb0120 article-title: Towards a complete 3D morphable model of the human head publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 222 start-page: 178 year: 2013 end-page: 192 ident: bb0030 article-title: Infant growth patterns of the mandible in modern humans: a closer exploration of the developmental interactions between the symphyseal bone, the teeth, and the suprahyoid and tongue muscle insertion sites publication-title: J. Anat. – volume: 1 start-page: 13 year: 2016 end-page: 26 ident: bb0025 publication-title: Feeding and Swallowing Issues in Infants With Craniofacial Anomalies. Perspectives of the ASHA Special Interest Groups – volume: 20 start-page: 2512 year: 2010 end-page: 2517 ident: bb0070 article-title: Size, shape and age-related changes of the mandibular condyle during childhood publication-title: Eur. Radiol. – volume: 126 start-page: 233 year: 2018 end-page: 254 ident: bb0020 article-title: Large scale 3d morphable models publication-title: Int. J. Comput. Vis. – volume: 80 start-page: 97 year: 2010 end-page: 105 ident: bb0105 article-title: Mandibular growth, remodeling, and maturation during infancy and early childhood publication-title: Angle Orthod. – start-page: 404 year: 2018 end-page: 408 ident: bb0040 article-title: A data-augmented 3D morphable model of the ear publication-title: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) – volume: 4 start-page: 91 year: 2008 end-page: 99 ident: bb0050 article-title: Mandibular morphology as an indicator of human subadult age: geometric morphometric approaches publication-title: Forensic Sci. Med. Pathol. – volume: 4 year: 2016 ident: bb0145 article-title: Surgical classification of the mandibular deformity in craniofacial microsomia using 3-dimensional computed tomography publication-title: Plast. Reconstr. Surg. Glob. Open – start-page: 2540 year: 2015 end-page: 2548 ident: bb0080 article-title: Learning an efficient model of hand shape variation from depth images publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition – start-page: 19 year: 2020 ident: bb0150 article-title: The morphology of the human mandible: a computational modelling study publication-title: Biomech. Model. Mechanobiol. – volume: 126 start-page: 233 year: 2018 ident: 10.1016/j.bonr.2022.101528_bb0020 article-title: Large scale 3d morphable models publication-title: Int. J. Comput. Vis. doi: 10.1007/s11263-017-1009-7 – volume: 1 start-page: 13 year: 2016 ident: 10.1016/j.bonr.2022.101528_bb0025 – volume: 10 year: 2015 ident: 10.1016/j.bonr.2022.101528_bb0100 article-title: A statistical skull geometry model for children 0–3 years old publication-title: PLoS One – start-page: 3085 year: 2017 ident: 10.1016/j.bonr.2022.101528_bb0035 article-title: A 3d morphable model of craniofacial shape and texture variation – volume: 78 issue: 822 year: 2020 ident: 10.1016/j.bonr.2022.101528_bb0055 article-title: A novel geometric morphometric analytical method for classifying mandibular morphology in infants with isolated Pierre Robin sequence publication-title: J. Oral Maxillofac. Surg. – volume: 77 start-page: 27 year: 2017 ident: 10.1016/j.bonr.2022.101528_bb0075 article-title: Characterizing mandibular growth using three-dimensional imaging techniques and anatomic landmarks publication-title: Arch. Oral Biol. doi: 10.1016/j.archoralbio.2017.01.018 – start-page: 2540 year: 2015 ident: 10.1016/j.bonr.2022.101528_bb0080 article-title: Learning an efficient model of hand shape variation from depth images – volume: 7 start-page: 425 year: 2003 ident: 10.1016/j.bonr.2022.101528_bb0060 article-title: Growth modeling of human mandibles using non-euclidean metrics publication-title: Med. Image Anal. doi: 10.1016/S1361-8415(03)00034-3 – volume: 217 issue: 233 year: 2012 ident: 10.1016/j.bonr.2022.101528_bb0065 article-title: An assessment of early mandibular growth publication-title: Forensic Sci. Int. – volume: 116 start-page: 14e year: 2005 ident: 10.1016/j.bonr.2022.101528_bb0135 article-title: The pediatric mandible: I. A primer on growth and development publication-title: Plast. Reconstr. Surg. doi: 10.1097/01.PRS.0000169940.69315.9C – volume: 4 year: 2016 ident: 10.1016/j.bonr.2022.101528_bb0145 article-title: Surgical classification of the mandibular deformity in craniofacial microsomia using 3-dimensional computed tomography publication-title: Plast. Reconstr. Surg. Glob. Open doi: 10.1097/GOX.0000000000000582 – start-page: 187 year: 1999 ident: 10.1016/j.bonr.2022.101528_bb0010 article-title: A morphable model for the synthesis of 3D faces – ident: 10.1016/j.bonr.2022.101528_bb0115 – start-page: 1 year: 2021 ident: 10.1016/j.bonr.2022.101528_bb0130 article-title: Modelling growth curves of the normal infant’s mandible: 3D measurements using computed tomography publication-title: Clin. Oral Investig. – start-page: 5543 year: 2016 ident: 10.1016/j.bonr.2022.101528_bb0015 article-title: A 3d morphable model learnt from 10,000 faces – volume: 80 start-page: 97 year: 2010 ident: 10.1016/j.bonr.2022.101528_bb0105 article-title: Mandibular growth, remodeling, and maturation during infancy and early childhood publication-title: Angle Orthod. doi: 10.2319/020309-67.1 – volume: 207 start-page: 669 year: 2005 ident: 10.1016/j.bonr.2022.101528_bb0095 article-title: Three-dimensional analysis of mandibular growth and tooth eruption publication-title: J. Anat. doi: 10.1111/j.1469-7580.2005.00479.x – start-page: 19 year: 2020 ident: 10.1016/j.bonr.2022.101528_bb0150 article-title: The morphology of the human mandible: a computational modelling study publication-title: Biomech. Model. Mechanobiol. – start-page: 404 year: 2018 ident: 10.1016/j.bonr.2022.101528_bb0040 article-title: A data-augmented 3D morphable model of the ear – volume: 28 start-page: 921 year: 1941 ident: 10.1016/j.bonr.2022.101528_bb0140 article-title: The mandibular angle in infancy: its significance and modification publication-title: J. Am. Dent. Assoc. doi: 10.14219/jada.archive.1941.0157 – volume: Vols 1-8 year: 2007 ident: 10.1016/j.bonr.2022.101528_bb0005 article-title: Optimal step nonrigid ICP algorithms for surface registration – volume: 9 start-page: 1 year: 2019 ident: 10.1016/j.bonr.2022.101528_bb0090 article-title: A machine learning framework for automated diagnosis and computer-assisted planning in plastic and reconstructive surgery publication-title: Sci. Rep. doi: 10.1038/s41598-019-49506-1 – volume: 20 start-page: 2512 year: 2010 ident: 10.1016/j.bonr.2022.101528_bb0070 article-title: Size, shape and age-related changes of the mandibular condyle during childhood publication-title: Eur. Radiol. doi: 10.1007/s00330-010-1828-1 – start-page: 1771 year: 2016 ident: 10.1016/j.bonr.2022.101528_bb0155 article-title: Generating a morphable model of ears – volume: 170 start-page: 496 year: 2019 ident: 10.1016/j.bonr.2022.101528_bb0125 article-title: Morphometric characterization of the very young child mandibular growth pattern: what happen before and after the deciduous dentition development? publication-title: Am. J. Phys. Anthropol. doi: 10.1002/ajpa.23933 – volume: 52 start-page: 6 year: 2007 ident: 10.1016/j.bonr.2022.101528_bb0045 article-title: Sexual dimorphism in the subadult mandible: quantification using geometric morphometrics publication-title: J. Forensic Sci. doi: 10.1111/j.1556-4029.2006.00311.x – volume: 43 start-page: 4142 issue: 11 year: 2020 ident: 10.1016/j.bonr.2022.101528_bb0120 article-title: Towards a complete 3D morphable model of the human head publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2020.2991150 – volume: 4 start-page: 91 year: 2008 ident: 10.1016/j.bonr.2022.101528_bb0050 article-title: Mandibular morphology as an indicator of human subadult age: geometric morphometric approaches publication-title: Forensic Sci. Med. Pathol. doi: 10.1007/s12024-007-9015-7 – volume: 141 year: 2020 ident: 10.1016/j.bonr.2022.101528_bb0110 article-title: Early mandibular morphological differences in patients with FGFR2 and FGFR3-related syndromic craniosynostoses: a 3D comparative study publication-title: Bone doi: 10.1016/j.bone.2020.115600 – volume: 222 start-page: 178 year: 2013 ident: 10.1016/j.bonr.2022.101528_bb0030 article-title: Infant growth patterns of the mandible in modern humans: a closer exploration of the developmental interactions between the symphyseal bone, the teeth, and the suprahyoid and tongue muscle insertion sites publication-title: J. Anat. doi: 10.1111/joa.12008 – volume: 11 start-page: 18843 year: 2021 ident: 10.1016/j.bonr.2022.101528_bb0085 article-title: A three-dimensional statistical shape model of the growing mandible publication-title: Sci. Rep. doi: 10.1038/s41598-021-98421-x |
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| Snippet | AbstractBackground/aimTo develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.... To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. Computed tomography... To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.Background/aimTo... • Shape and development patterns of the paediatric mandible (0 – 4 years) were evaluated using a dataset of 242 CT scans. • A 3D morphable model of the... Background/aim: To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.... |
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| SubjectTerms | 3D morphable model Full Length Infant mandible Morphometrics Orthopedics Paediatric mandible Partial least squares Statistical model |
| Title | Growth patterns and shape development of the paediatric mandible – A 3D statistical model |
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