Upper airway segmentation and measurement in MRI using fuzzy connectedness

Jianguo Liu; Jayaram K. Udupa; Dewey Odhner; Joe M. McDonough; Raanan Arens

doi:10.1117/12.463588

24 April 2002 Upper airway segmentation and measurement in MRI using fuzzy connectedness

Jianguo Liu, Jayaram K. Udupa, Dewey Odhner, Joe M. McDonough, Raanan Arens

Proceedings Volume 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images; (2002) https://doi.org/10.1117/12.463588
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

The purpose of this work is to build a computerized system for the delineation of upper airway structures via MRI and to evaluate its effectiveness for routine clinical use in aiding diagnosis of upper airway disorders in children. We use two MRI protocols, axial T1 and T2, to gather information about different aspects of the airway and its surrounding soft tissue structures including adenoid, tonsils, tongue and soft palate. These images are processed and segmented to compute the architectural parameters of the airway such as its surface description, volume, central (medial) line, and cross-sectional areas at planes orthogonal to the central line. We have built a software package based on 3DVIEWNIX and running on a 450 MHz Pentium PC under Linux system (and on a Sun workstation under Unix) for the various operations of visualization, segmentation, registration, prefiltering, interpolation, standardization, and quantitative analysis of the airway. The system has been tested utilizing 40 patient studies. For every study, the system segmented and displayed a smooth 3D rendition of the airway, its central line and a plot of the cross-sectional area of the airway orthogonal to the central line as a function of the distance from one end of the central line. The tests indicate 97% precision and accuracy for segmentation. The mean time taken per study is about 4 minutes for the airway. This includes operator interaction time and processing time. This method provides a robust and fast means of assessing the airway size, shape, and places of restriction, as well as providing a structural data set suitable for use in modeling studies of airflow and mechanics.

Citation Download Citation

Jianguo Liu, Jayaram K. Udupa, Dewey Odhner, Joe M. McDonough, and Raanan Arens "Upper airway segmentation and measurement in MRI using fuzzy connectedness", Proc. SPIE 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images, (24 April 2002); https://doi.org/10.1117/12.463588

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