System for Upper Airway Segmentation and Measurement with MR Imaging and Fuzzy Connectedness

Liu, Jianguo; Udupa, Jayaram K.; Odhnera, Dewey; McDonough, Joseph M.; Arens, Raanan

doi:10.1016/S1076-6332(03)80783-3

« Previous Next »Academic Radiology
Volume 10, Issue 1 , Pages 13-24, January 2003

System for Upper Airway Segmentation and Measurement with MR Imaging and Fuzzy Connectedness☆

Jianguo Liu, PhD
- Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Dr, 19104-6021, Philadelphia, PA, USA
Jayaram K. Udupa, PhD
- Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Dr, 19104-6021, Philadelphia, PA, USA
- Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Dr, Philadelphia, PA 19104-6021
Dewey Odhnera, MA
- Medical Image Processing Group, Department of Radiology, University of Pennsylvania, 4th Floor, Blockley Hall, 423 Guardian Dr, 19104-6021, Philadelphia, PA, USA
Joseph M. McDonough, MS
- Children's Hospital of Philadelphia, Pa, USA
Raanan Arens, MD
- Children's Hospital of Philadelphia, Pa, USA

Received 19 August 2002; received in revised form 24 August 2002; accepted 26 August 2002.

Abstract

Rationale and Objectives

The purpose of this study was to evaluate whether a computerized system developed to help delineate the upper airway and surrounding structures with magnetic resonance (MR) imaging was effective for aiding in the diagnosis of upper airway disorders in children.

Materials and Methods

The authors performed axial T2-weighted MR imaging to gather information about different aspects of the airway and its surrounding soft-tissue structures, including the adenoid and palatine tonsils, tongue, and soft palate. Images were processed and segmented to compute the architectural parameters of the airway (eg, surface description, volume, central [medial] line, and cross-sectional areas at planes perpendicular to the central line). The authors built a software package for the visualization, segmentation, registration, prefiltering, interpolation, standardization, and quantitative analysis of the airway and tonsils.

Results

The system was tested with 40 patient studies. For every study, the system segmented and displayed a smooth three-dimensional rendition of the airway and 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 precision and accuracy for segmentation was 97%. The mean time taken per study was about 4 minutes and included the operator interaction time and processing time.

Conclusion

This method provides a robust and fast means of assessing the airway size, shape, and level of restriction, as well as a structural data set suitable for use in modeling studies of airflow and mechanics.

Keywords: Magnetic resonance (MR), image processing, bronchi, anatomy