## 5 Conclusions  
In this research, a system was designed for the nasal cavity three-dimensional structure reconstruction, including the lower computer of a nasal acoustic signal acquisition device and the upper computer of nasal acoustic signal analysis software. The original nasal acoustic signal was obtained by the lower computer of the nasal acoustic signal acquisition device, based on a short-source acoustic tube. The incident and reflected waves were separated from the original nasal acoustic signal according to the propagation characteristics of the acoustic wave in the short-source acoustic tube. The influence of the DC offset component and high-frequency noise on the accuracy of the nasal cavity three-dimensional structure reconstruction was analyzed. After multiple experiments and analysis, the DC offset component was eliminated, and the high-frequency noise was suppressed by introducing the constraint factor \(q\), which is the most important factor for the reconstruction of the nasal cavity. The results show that the accuracy of the nasal cavity three-dimensional structure reconstruction is improved under this system, and the upper computer software is designed to visualize and display the data of the nasal cavity two-dimensional depth-cross-sectional area curves, the nasal cavity three-dimensional structure reconstruction model, and the cross-sectional area values of key points.  
The system of this article applies to a nasal cavity three-dimensional structure reconstruction based on a short-source acoustic tube. In actual applications, this system automatically processes and analyzes the collected data, suppressing the impact of high-frequency noise and the DC offset component to better reconstruct the patient's nasal structure. At present, there are still some problems with nasal cavity three-dimensional structure reconstruction based on the acoustic wave reflection method. Building on the foundation laid by this research, the accuracy of the system can be further improved by several methods. First, the impact of low-frequency noise also needs to be considered. However, the removal of low-frequency noise is difficult. In addition, the nasal cavity three-dimensional structure hierarchical reconstruction method relies on past data and has an effect of error accumulation. These are the difficulties that still need to be overcome in nasal cavity three-dimensional structure hierarchical reconstruction methods.  
Figure 17: (**a**) Lower computer parameter configuration interface. (**b**) Data acquisition interface. (**c**) Single test result analysis interface. (**d**) Multiple left and right nasal cavities test result comparison analysis interface. (**e**) Nasal cavity three-dimensional structure reconstruction interface.  
**Author Contributions:** Conceptualization, X.L., G.M. and C.G.; methodology, X.L., G.M. and C.G.; software, X.L., G.M. and Y.W. ([PERSON]); validation, X.L. and G.M.; formal analysis, C.G.; investigation, G.M. and Y.W. ([PERSON]); resources, X.L. and C.G.; data curation, Y.W. ([PERSON]), G.M. and W.G.; writing--original draft preparation, X.L., G.M. and C.G.; writing--review and editing, X.L., G.M. and C.G.; visualization, G.M.; supervision, C.G., Y.G. and J.L.; project administration, X.L. and C.G.; funding acquisition, X.L. and C.G. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Beijing Natural Science Foundation (No. 6214034).  
**Institutional Review Board Statement:** Not applicable.  
**Infrared Consent Statement:** Not applicable.  
**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to their containing information that could compromise the privacy of research participants.  
**Conflicts of Interest:** The authors declare no conflicts of interest.