Predictive Statistical Model of Early Cranial Development

• Published in: IEEE transactions on biomedical engineering Vol. 69; no. 2; pp. 537 - 546
• Main Authors: PorrasPerez, Antonio Reyes, Keating, Robert, Lee, Janice, Linguraru, Marius George
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.02.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: bilinear PCA; Bones; Brain modeling; Calvaria; Child, Preschool; Computed tomography; Cranial; cranial bone development; Cranial growth; Cranial sutures; Cross-Sectional Studies; Datasets; Growth patterns; head CT; Humans; Mathematical models; Model accuracy; Models, Statistical; Prediction models; Principal components analysis; Shape; Skull; Skull - diagnostic imaging; Sociology; Spatial analysis; spatiotemporal statistical model; Statistical models; Statistical prediction; Statistics; Tomography, X-Ray Computed - methods
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2021.3100745

Objective: We present a data-driven method to build a spatiotemporal statistical shape model predictive of normal cranial growth from birth to the age of 2 years. Methods: The model was constructed using a normative cross-sectional computed tomography image dataset of 278 subjects. First, we propose...