Three-dimensional reconstruction of trachea using computed tomography imaging as therapy for tracheal stenosis in infants.

Background And Objective: In this study, we aim to develop a system that uses computed tomography (CT) imaging for three-dimensional (3D) reconstruction of the trachea as therapy for tracheal stenosis in infants, and further calculate the cross-sectional area and volume, assisting doctors in clinical diagnosis.

Methods: We first used image processing, calculating the cross-sectional area and volume. We used the improved median filter for image processing and designed the system for capturing the cross-sectional area of endotracheal tube. We then established 3D reconstruction images with isosurface extraction technology and calculated the cross-sectional area and volume. Medical indicator data analysis was performed.

Results: The median filter developed in this study performed better in filtering speckle noise compared to traditional filtering methods. Furthermore, the median filter can keep fine texture feature, so that the subsequent contour selection and 3D reconstructed volume are more accurate. We also proposed new medical grading indexes according to tracheal obstruction volume ratio to assist doctors with the diagnosis and provide recommendations on treatment. Seventeen samples were examined in this study. Four sections of each sample are reviewed. Sixty-eight sections were used for validation, and the overall accuracy is very reliable.

Conclusions: Using image processing we obtained tracheal CT images before 3D reconstruction and calculated the cross-sectional area and volume of the trachea. New medical indicators are proposed according to the location and severity of stenosis to assist doctors with diagnosis.