The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model.

In this paper, we investigate the heating function of the nasal cavity qualitatively, using a high-quality, large-scale statistical shape model. This model consists of a symmetrical and an asymmetrical part and provides a new and unique way of examining changes in nasal heating function resulting from natural variations in nasal shape (as obtained from 100 clinical CT scans). Data collected from patients suffering from different nasal or sinus-related complaints are included. Parameterized models allow us to investigate the effect of continuous deviations in shape from the mean nasal cavity. This approach also enables us to avoid many of the compounded effects on flow and heat exchange, which one would encounter when comparing different patient-specific models. The effects of global size, size-related features, and turbinate size are investigated using the symmetrical shape model. The asymmetrical model is used to investigate different types of septal deviation using Mladina's classification. The qualitative results are discussed and compared with findings from the existing literature.

Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling.

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.