ArticleRoyal Society open science2018
High quality statistical shape modelling of the human nasal cavity and applications.
Article in Royal Society open science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 23 citations in OpenAlex.
- HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing.Computer methods in applied mechanics and engineering · 2026Article
- Standardization of nasal airway structure model of Chinese Han nationality for characterization of nasal formulation spatial deposition atlases.Acta pharmaceutica Sinica. B · 2025Article
- New insights into the variability of upper airway morphology in modern humans.Journal of anatomy · 2023Article
- Volumetric measurement of paranasal sinuses and its clinical significance in pituitary neuroendocrine tumors operated using an endoscopic endonasal approach.Frontiers in neurology · 2023Article
- Toward automatic atlas-based surgical planning for septoplasty.International journal of computer assisted radiology and surgery · 2022Article
- CT-Based Analysis of Left Ventricular Hemodynamics Using Statistical Shape Modeling and Computational Fluid Dynamics.Frontiers in cardiovascular medicine · 2022Article
- Effect of septal deviation on nasomaxillary shape: A geometric morphometric study.Journal of anatomy · 2021Article
- Micro-CT of the human ossicular chain: Statistical shape modeling and implications for otologic surgery.Journal of anatomy · 2021Article
- Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity.Scientific reports · 2020Article
- Anatomical Workspace Study of Endonasal Endoscopic Transsphenoidal Approach.Open medicine (Warsaw, Poland) · 2019Article
- High quality statistical shape modelling of the human nasal cavity and applications.Royal Society open science · 2018Article
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human nose is a complex organ that shows large morphological variations and has many important functions. However, the relation between shape and function is not yet fully understood. In this work, we present a high quality statistical shape model of the human nose based on clinical CT data of 46 patients. A technique based on cylindrical parametrization was used to create a correspondence between the nasal shapes of the population. Applying principal component analysis on these corresponded nasal cavities resulted in an average nasal geometry and geometrical variations, known as principal components, present in the population with a high precision. The analysis led to 46 principal components, which account for 95% of the total geometrical variation captured. These variations are first discussed qualitatively, and the effect on the average nasal shape of the first five principal components is visualized. Hereafter, by using this statistical shape model, two application examples that lead to quantitative data are shown: nasal shape in function of age and gender, and a morphometric analysis of different anatomical regions. Shape models, as the one presented here, can help to get a better understanding of nasal shape and variation, and their relationship with demographic data.
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