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Updated: Dec 7, 2025

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Evaluation of the Midface by Statistical Shape Modeling.

Thomas Hierl¹, Hans-Martin Doerfler², Heike Huempfner-Hierl³

¹Head of Department, Department of Oral & Maxillofacial Plastic Surgery, Helios Vogtland-Klinikum Plauen, Plauen, Germany.

Journal of Oral and Maxillofacial Surgery : Official Journal of the American Association of Oral and Maxillofacial Surgeons

|September 24, 2020

Summary

This study generated a statistical shape model (SSM) of the midface, revealing high symmetry and distinct gender differences in facial morphology. Bone thickness analysis offers insights for surgical planning.

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Area of Science:

Medical imaging and computational anatomy.
Biomechanical analysis of craniofacial structures.

Background:

Understanding midface morphology is crucial for reconstructive surgery and anthropological studies.
Statistical Shape Models (SSMs) provide a quantitative framework for analyzing anatomical variations.

Purpose of the Study:

To develop a statistical shape model (SSM) of the human midface.
To evaluate midface symmetry, gender-specific characteristics, and bone thickness using the SSM.

Main Methods:

Analysis of 102 computed tomography (CT) scans.
Application of segmentation, landmarking, and principal component analysis (PCA) for SSM creation.
Visualization of symmetry and gender differences via registration and color-coding; bone thickness calculated from surface distances.

Main Results:

The generated SSM demonstrated high symmetry across all models.
Significant gender differences were observed, with males exhibiting a more prominent forehead, nasal bones, and wider bizygomatic dimensions.
Calculated bone thickness aligned with established concepts of maxillary pillars and buttresses.

Conclusions:

SSMs are effective tools for analyzing midface morphology and aiding virtual surgical planning.
Bone thickness quantification derived from SSMs can enhance surgical planning and biomechanical assessments.