Segmentation and visualization of tissues surrounding the airway in children via MRI

Abstract

Continuing with our previous work of the segmentation and delineation of upper airway, the purpose of this work is to segment and delineate soft tissue organs surrounding the upper airway, such as adenoid, tonsils, fat pads and tongue, with the further goal of studying the relationship among the architectures of these structures, for understanding upper airway disorders in children. We use two MRI protocols, Axial T2 (used for adenoid, tonsil, and fat pads) and sagittal T1 (for tongue), to gather information about different aspects of the tissues. MR images are first corrected for background intensity variation and then the intensities are standardized. All segmentations are achieved via fuzzy connectedness algorithms with only limited operator interaction. A smooth 3D rendition of the upper airway and its surrounding tissues is displayed. The system has been tested utilizing 20 patient data sets. The tests indicate a 95% or better precision and accuracy for segmentation. The mean time taken per study is about 15 minutes including operator interaction time and processing time for all operations. This method provides a robust and fast means of assessing sizes, shapes, and the architecture of the tissues surrounding the upper airway, as well as providing data sets suitable for use in modeling studies of airflow and mechanics.