Standardization of Thresholding for Binary Conversion of Vocal Tract Modeling in Computed Tomography

Postoperative head and neck cancer patients suffer from speech disorders, which are the result of changes in their vocal tracts. Making a solid vocal tract model and measuring its transmission characteristics will provide one of the most useful tools to resolve the problem. In binary conversion of X-ray computed tomographic (CT) images for vocal tract reconstruction, nonobjective methods have been used by many researchers. We hypothesized that a standardized vocal tract model could be reconstructed by adopting the Hounsfield number of fat tissue as a criterion for thresholding of binary conversion, because its Hounsfield number is the nearest to air in the human body. The purpose of this study was to establish a new standardized method for binary conversion in reconstructing three-dimensional (3-D) vocal tract models. CT images for postoperative diagnosis were secondarily obtained from a CT scanner. Each patientʹs minimum settings of Hounsfield number for the buccal fat-pad regions were measured. Thresholds were set every 50 Hounsfield units (HU) from the bottom line of the buccal fat-pad region to −1024آ HU, the images were converted into binary values, and were evaluated according to the three-grade system based on anatomically defined criteria. The optimal threshold between tissue and air was determined by nonlinear multiple regression analyses. Each patientʹs minimum settings of the buccal fat-pad regions were obtained. The optimal threshold was determined to be −165آ HU from each patientʹs minimum settings of the Hounsfield number for the buccal fat-pad regions. To conclude, a method of 3-D standardized vocal tract modeling was established.