{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T07:20:34Z","timestamp":1789456834447,"version":"build-2803163510"},"reference-count":67,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:00:00Z","timestamp":1772150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shaanxi Program on Key Research and Development Projects","award":["2018SF-031"],"award-info":[{"award-number":["2018SF-031"]}]},{"name":"Shaanxi Provincial Clinical Research Center for Dental Diseases","award":["2020YHJB10"],"award-info":[{"award-number":["2020YHJB10"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Background: Childhood and adolescence constitute a critical period for craniofacial growth. Understanding its developmental patterns is essential for clinical decision-making in orthodontics and maxillofacial surgery. Traditional cephalometric analysis relies on manual landmarking, which oversimplifies complex morphology and introduces subjectivity. Although deep learning, a key artificial intelligence (AI) technology, has demonstrated remarkable performance in image analysis and classification, most methods still depend on manual annotations during training, perpetuating subjectivity and limiting model generalizability and robustness on large datasets. This hinders the development of objective, comprehensive methods to quantify craniofacial growth that account for its multi-tissue complexity. Methods: To address these limitations, this study developed an end-to-end deep learning framework based on lateral cephalometric radiographs from 41,625 individuals aged 4\u201318 years. Without relying on manual annotations, the model is designed to autonomously extract dynamic imaging features associated with continuous age intervals in craniofacial development and further discern features related to sexual dimorphism. Gradient-weighted Class Activation Mapping (Grad-CAM) was employed to visualize the learned features, generating population-averaged saliency maps that highlight age-related and sex-related patterns. Furthermore, we introduced two novel quantitative metrics, the Age-related Saliency Index (ASI) and the Sex-related Saliency Index (SSI), to evaluate the significance of developmental and dimorphic characteristics in key craniofacial regions. Results: Age-related saliency maps extended the focus from external contours to internal anatomical details of the bones, intuitively visualizing the relative importance of multiple bone regions during dynamic development, with the ASI providing a quantitative prioritization of these regions. The Sex-related Saliency Index (SSI) quantified the dynamic evolution of sexual dimorphism, demonstrating that early-stage differences were widely distributed across cranial bones and gradually became concentrated in the mandibular region by adulthood. Conclusions: This study established an end-to-end deep learning framework for analyzing large-scale lateral cephalometric radiographs. By generating age- and sex-related average saliency maps and their corresponding quantitative indices, we visualized and quantified the spatiotemporal growth dynamics and sexual dimorphism across distinct craniofacial skeletal regions throughout development. These findings not only validate established developmental theories but also provide novel insights into the coordinated growth patterns of craniofacial bones and sex-specific radiological characteristics, offering clinicians objective quantitative references for assessing developmental stages and guiding the timing of interventions targeting specific craniofacial regions.<\/jats:p>","DOI":"10.3390\/bioengineering13030277","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T10:41:02Z","timestamp":1772188862000},"page":"277","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Quantification of Craniofacial Growth Pattern Based on Deep Learning"],"prefix":"10.3390","volume":"13","author":[{"given":"Ziyi","family":"Hu","sequence":"first","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuyanran","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5590-3229","authenticated-orcid":false,"given":"Ningtao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer, Luoyang Institate of Science and Technology, Luoyang 471023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1742-5119","authenticated-orcid":false,"given":"Xin","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyu","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanglin","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8176-638X","authenticated-orcid":false,"given":"Zhiyong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuang","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Department of Stomatology, College of Stomatology, Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"},{"name":"Department of Orthodontics, Affiliated Stomatological Hospital of Xi\u2019an Jiaotong University, Xi\u2019an 710004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1002\/ar.22918","article-title":"Variation in timing, duration, intensity, and direction of adolescent growth in the mandible, maxilla, and cranial base: The Fels longitudinal study","volume":"297","author":"Nahhas","year":"2014","journal-title":"Anat. Rec."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/S0011-8532(22)01741-4","article-title":"Craniofacial growth","volume":"44","author":"Ranly","year":"2000","journal-title":"Dent. Clin. N. Am."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1111\/j.1469-7580.2006.00644.x","article-title":"Craniofacial levels and the morphological maturation of the human skull","volume":"209","author":"Bastir","year":"2006","journal-title":"J. Anat."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.coms.2020.01.007","article-title":"Craniofacial Growth: Current Theories and Influence on Management","volume":"32","author":"Manlove","year":"2020","journal-title":"Oral Maxillofac. Surg. Clin. N. Am."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.coms.2012.05.007","article-title":"Growth and development considerations for craniomaxillofacial surgery","volume":"24","author":"Costello","year":"2012","journal-title":"Oral Maxillofac. Surg. Clin. N. Am."},{"key":"ref_6","first-page":"23","article-title":"Craniofacial growth: Evolving paradigms","volume":"33","author":"Castaldo","year":"2015","journal-title":"Cranio J. Craniomandib. Pract."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1179\/bjo.4.2.53","article-title":"Growth of the maxilla in three dimensions as revealed radiographically by the implant method","volume":"4","author":"Skieller","year":"1977","journal-title":"Br. J. Orthod."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1093\/ejo\/cjp147","article-title":"Natural reference structures in the human mandible: A systematic search in children with tantalum implants","volume":"32","author":"Springate","year":"2010","journal-title":"Eur. J. Orthod."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1034\/j.1600-0544.2001.040305.x","article-title":"The nature of human craniofacial growth studied with finite element analytical approach","volume":"4","author":"Takeshita","year":"2001","journal-title":"Clin. Orthod. Res."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Thomas, O.O., Shen, H., Raaum, R.L., Harcourt-Smith, W.E.H., Polk, J.D., and Hasegawa-Johnson, M. (2023). Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics. PLoS Comput. Biol., 19.","DOI":"10.1371\/journal.pcbi.1009061"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1002\/ajpa.24531","article-title":"Thirty years of geometric morphometrics: Achievements, challenges, and the ongoing quest for biological meaningfulness","volume":"178","author":"Mitteroecker","year":"2022","journal-title":"Am. J. Biol. Anthropol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1016\/j.ajodo.2015.12.011","article-title":"Reconsidering \u201cThe inappropriateness of conventional cephalometrics\u201d","volume":"149","author":"Bookstein","year":"2016","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s11604-018-0726-3","article-title":"Deep learning with convolutional neural network in radiology","volume":"36","author":"Yasaka","year":"2018","journal-title":"jpn. J. Radiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"104115","DOI":"10.1016\/j.jdent.2022.104115","article-title":"Deep learning for caries detection: A systematic review","volume":"122","author":"Motamedian","year":"2022","journal-title":"J. Dent."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Li, X., Zhao, D., Xie, J., Wen, H., Liu, C., Li, Y., Li, W., and Wang, S. (2023). Deep learning for classifying the stages of periodontitis on dental images: A systematic review and meta-analysis. BMC Oral Health, 23.","DOI":"10.1186\/s12903-023-03751-z"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chun, S.Y., Kang, Y.H., Yang, S., Kang, S.R., Lee, S.J., Kim, J.M., Kim, J.E., Huh, K.H., Lee, S.S., and Heo, M.S. (2023). Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network. BMC Oral Health, 23.","DOI":"10.1186\/s12903-023-03496-9"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"102444","DOI":"10.1016\/j.media.2022.102444","article-title":"Recent advances and clinical applications of deep learning in medical image analysis","volume":"79","author":"Chen","year":"2022","journal-title":"Med. Image Anal."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.job.2022.03.003","article-title":"Deep learning models in medical image analysis","volume":"64","author":"Tsuneki","year":"2022","journal-title":"J. Oral Biosci."},{"key":"ref_19","first-page":"154","article-title":"CDSNet: An automated method for assessing growth stages from various anatomical regions in lateral cephalograms based on deep learning","volume":"14","author":"Zhang","year":"2025","journal-title":"J. World Fed. Orthod."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhou, J., Zhou, H., Pu, L., Gao, Y., Tang, Z., Yang, Y., You, M., Yang, Z., Lai, W., and Long, H. (2021). Development of an Artificial Intelligence System for the Automatic Evaluation of Cervical Vertebral Maturation Status. Diagnostics, 11.","DOI":"10.3390\/diagnostics11122200"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"103715","DOI":"10.1016\/j.media.2025.103715","article-title":"Attend-and-Refine: Interactive keypoint estimation and quantitative cervical vertebrae analysis for bone age assessment","volume":"106","author":"Kim","year":"2025","journal-title":"Med. Image Anal."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1002\/ar.24736","article-title":"A human craniofacial life-course: Cross-sectional morphological covariations during postnatal growth, adolescence, and aging","volume":"305","author":"Jeffery","year":"2022","journal-title":"Anat. Rec."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2374","DOI":"10.1109\/TMI.2020.2968765","article-title":"Deep Neural Networks for Chronological Age Estimation From OPG Images","volume":"39","author":"Carreira","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1038\/s41746-022-00681-y","article-title":"Ageing and degeneration analysis using ageing-related dynamic attention on lateral cephalometric radiographs","volume":"5","author":"Zhang","year":"2022","journal-title":"npj Digit. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4771","DOI":"10.1038\/s41598-018-22752-5","article-title":"Modelling 3D craniofacial growth trajectories for population comparison and classification illustrated using sex-differences","volume":"8","author":"Matthews","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., and Batra, D. (2017, January 22\u201329). Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3235","DOI":"10.1002\/hbm.25011","article-title":"From a deep learning model back to the brain-Identifying regional predictors and their relation to aging","volume":"41","author":"Levakov","year":"2020","journal-title":"Hum. Brain Mapp."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"102486","DOI":"10.1016\/j.bspc.2021.102486","article-title":"A review on cephalometric landmark detection techniques","volume":"66","author":"Juneja","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_29","first-page":"399","article-title":"Skeletal malocclusion: A developmental disorder with a life-long morbidity","volume":"6","author":"Joshi","year":"2014","journal-title":"J. Clin. Med. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1177\/0022034515581643","article-title":"Candidate Gene Analyses of Skeletal Variation in Malocclusion","volume":"94","author":"Miller","year":"2015","journal-title":"J. Dent. Res."},{"key":"ref_31","first-page":"103","article-title":"Assessing growth and development of the facial profile","volume":"25","author":"Darwis","year":"2003","journal-title":"Pediatr. Dent."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"347","DOI":"10.12659\/PJR.895921","article-title":"Radiological Indicators of Bone Age Assessment in Cephalometric Images","volume":"81","author":"Derwich","year":"2016","journal-title":"Review. Pol. J. Radiol."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Yu, C., Hung, P.H., Hong, J.H., and Chiang, H.Y. (2023, January 10\u201313). Efficient Max Pooling Architecture with Zero-Padding for Convolutional Neural Networks. Proceedings of the 2023 IEEE 12th Global Conference on Consumer Electronics (GCCE), Nara, Japan.","DOI":"10.1109\/GCCE59613.2023.10315268"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1186\/s40537-019-0263-7","article-title":"Enlarging smaller images before inputting into convolutional neural network: Zero-padding vs. interpolation","volume":"6","author":"Hashemi","year":"2019","journal-title":"J. Big Data"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Kumar, R.R., and Gupta, S. (2024, January 4\u20136). Gender Recognizer: Leveraging Convolutional Neural Networks for Enhanced Performance. Proceedings of the 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit), Greater Noida, India.","DOI":"10.1109\/GlobalAISummit62156.2024.10947780"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Solomou, C., and Kazakov, D. (2021, January 16\u201317). Utilizing Chest X-rays for Age Prediction and Gender Classification. Proceedings of the 2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia.","DOI":"10.1109\/ISRITI54043.2021.9702796"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1597\/1545-1569_2000_037_0145_tdbbgs_2.3.co_2","article-title":"Three-dimensional Bolton-Brush Growth Study landmark data: Ontogeny and sexual dimorphism of the Bolton standards cohort","volume":"37","author":"Dean","year":"2000","journal-title":"Cleft Palate-Craniofacial J."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"50","DOI":"10.2319\/042110-215.1","article-title":"Age-related changes of the soft tissue profile from the second to the fourth decades of life","volume":"81","author":"Torlakovic","year":"2011","journal-title":"Angle Orthod."},{"key":"ref_39","first-page":"33","article-title":"Possibilities of Orthopedic Management of Pattern Ill Malocclusions During Growth","volume":"27","author":"Guedes","year":"2016","journal-title":"Int. J. Orthod."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1016\/j.ajodo.2013.01.019","article-title":"The pattern of facial skeletal growth and its relationship to various common indexes of maturation","volume":"143","author":"Mellion","year":"2013","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/S0889-5406(00)70251-4","article-title":"Maxillary and mandibular width changes studied using metallic implants","volume":"117","author":"Gandini","year":"2000","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_42","first-page":"54","article-title":"Longitudinal study of the growth of craniofacial widths in 13\u201318 years adolescents with normal occlusion","volume":"24","author":"Zhou","year":"2002","journal-title":"Acta Acad. Med. Sin."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1597\/1545-1569_1992_029_0118_csmboc_2.3.co_2","article-title":"Craniofacial skeletal measurements based on computed tomography: Part II. Normal values and growth trends","volume":"29","author":"Waitzman","year":"1992","journal-title":"Cleft Palate-Craniofacial J."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1016\/j.archoralbio.2010.05.012","article-title":"Incremental growth of the maxillary tuberosity from 6 to 20 years-A cross-sectional study","volume":"55","author":"Vardimon","year":"2010","journal-title":"Arch. Oral Biol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/S0889-5406(98)70287-2","article-title":"Age limitation on provision of orthopedic therapy and orthognathic surgery","volume":"113","author":"Weaver","year":"1998","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_46","first-page":"438","article-title":"Residual craniofacial growth: A cephalometric study of 50 cases","volume":"14","author":"Oualalou","year":"2016","journal-title":"Int. Orthod."},{"key":"ref_47","first-page":"127","article-title":"Late growth changes in the craniofacial skeleton","volume":"58","author":"Lewis","year":"1988","journal-title":"Angle Orthod."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.forsciint.2010.04.009","article-title":"Analysis of time of closure of the spheno-occipital synchondrosis using computed tomography","volume":"200","author":"Bassed","year":"2010","journal-title":"Forensic Sci. Int."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/S0889-5406(05)80052-6","article-title":"Facial growth in males 16 to 20 years of age","volume":"97","author":"Love","year":"1990","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/s13293-016-0076-8","article-title":"Using the 3D Facial Norms Database to investigate craniofacial sexual dimorphism in healthy children, adolescents, and adults","volume":"7","author":"Kesterke","year":"2016","journal-title":"Biol. Sex Differ."},{"key":"ref_51","first-page":"423","article-title":"Facial growth: Men and women differ","volume":"105","author":"Carels","year":"1998","journal-title":"Ned. Tijdschr. Voor Tandheelkd."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jchb.2015.10.001","article-title":"Sexual dimorphism in the facial morphology of adult humans: A three-dimensional analysis","volume":"67","author":"Tanikawa","year":"2016","journal-title":"Homo"},{"key":"ref_53","unstructured":"Loshchilov, I., and Hutter, F.J.A. (2017). Fixing Weight Decay Regularization in Adam. arXiv."},{"key":"ref_54","first-page":"90","article-title":"Growth of the main head dimensions from birth up to twenty years of age in Czechs","volume":"31","author":"Dokladal","year":"1959","journal-title":"Hum. Biol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1002\/dev.420070305","article-title":"Phrenoblysis: Special brain and mind growth periods. II. Human mental development","volume":"7","author":"Epstein","year":"1974","journal-title":"Dev. Psychobiol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1093\/ejo\/26.1.31","article-title":"Transverse development of the craniofacial skeleton and dentition between 7 and 15 years of age\u2014A longitudinal postero-anterior cephalometric study","volume":"26","author":"Lux","year":"2004","journal-title":"Eur. J. Orthod."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1007\/s00056-006-0533-9","article-title":"Proportional Growth of Craniofacial Regions","volume":"67","author":"Trenouth","year":"2006","journal-title":"J. Orofac. Orthop."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1002\/ajpa.24153","article-title":"Intraspecific variability in human maxillary bone modeling patterns during ontogeny","volume":"173","author":"Schuh","year":"2020","journal-title":"Am. J. Phys. Anthropol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"e70155","DOI":"10.1002\/ajpa.70155","article-title":"Exploring the Relationship Between Mandibular Morphology, Dental Eruption, and Chronological Age in Modern Human Juveniles Through Geometric Morphometrics","volume":"188","author":"Chakraborty","year":"2025","journal-title":"Am. J. Biol. Anthropol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.sleep.2021.08.011","article-title":"Cone beam CT evaluation of skeletal and nasomaxillary complex volume changes after rapid maxillary expansion in OSA children","volume":"86","author":"Pirelli","year":"2021","journal-title":"Sleep Med."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1016\/j.ajodo.2008.01.020","article-title":"Pharyngeal airway volume and shape from cone-beam computed tomography: Relationship to facial morphology","volume":"136","author":"Grauer","year":"2009","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/0002-9416(75)90158-X","article-title":"Palatal growth studied on human autopsy material. A histologic microradiographic study","volume":"68","author":"Melsen","year":"1975","journal-title":"Am. J. Orthod."},{"key":"ref_63","first-page":"47","article-title":"Sexual dimorphism in normal craniofacial growth","volume":"63","author":"Ursi","year":"1993","journal-title":"Angle Orthod."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"e93","DOI":"10.1016\/j.ajodo.2022.07.015","article-title":"Morphologic variations in the craniofacial structures in Japanese adults and their relationship with sex differences","volume":"163","author":"Yamamoto","year":"2023","journal-title":"Am. J. Orthod. Dentofac. Orthop."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1002\/ajpa.10023","article-title":"Thin-plate spline analysis of allometry and sexual dimorphism in the human craniofacial complex","volume":"117","author":"Rosas","year":"2002","journal-title":"Am. J. Phys. Anthropol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1007\/s00234-006-0140-x","article-title":"3D CT-based cephalometric analysis: 3D cephalometric theoretical concept and software","volume":"48","author":"Olszewski","year":"2006","journal-title":"Neuroradiology"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1093\/ejo\/cjv088","article-title":"A new mandible-specific landmark reference system for three-dimensional cephalometry using cone-beam computed tomography","volume":"38","author":"Pittayapat","year":"2016","journal-title":"Eur. J. Orthod."}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/13\/3\/277\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T11:20:52Z","timestamp":1772191252000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/13\/3\/277"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,27]]},"references-count":67,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["bioengineering13030277"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering13030277","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,27]]}}}