Publication
Title
Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling
Author
Abstract
The nose is a complex and important organ with a multitude of functions. Computational fluid dynamics (CFD) has been shown to be a valuable tool to obtain a better understanding of the functioning of the nose. CFD simulations require a surface geometry, which is constructed from tomographic data. This can be a very time-consuming task when one chooses to exclude the sinuses from the simulation domain, which in general keeps the size of the CFD model more manageable. In this work, an approach for the semi-automatic construction of the human nasal cavity is presented. In the first part, limited manual interaction is needed to create a coarse surface model. In the next part, this result is further refined based on the combination of active shape modeling with elastic surface deformation. The different steps are bundled in a Matlab toolbox with a graphical interface which guides the user. This interface allows easy manipulation of the data during intermediate steps, and also allows manual adjustments of the reconstructed nasal surface at the end. Two results are shown, and the approach and its precision are discussed. These results demonstrated that the followed approach can be used for the semi-automatic segmentation of a human nasal cavity from tomographic data, substantially reducing the amount of operator time.
Language
English
Source (journal)
Computers in biology and medicine. - Oxford
Computers in biology and medicine. - Oxford
Publication
Oxford : 2019
ISSN
0010-4825
Volume/pages
105 (2019) , p. 27-38
ISI
000458943300003
Pubmed ID
30576918
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Decision support system for objective nasal airway obstruction assessment using computational fluid dynamics
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 03.01.2019
Last edited 15.10.2021
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