Paper
9 March 2010 Automated segmentation of mucosal change in rhinosinusitis patients
William F. Sensakovic, Jayant M. Pinto, Faud M. Baroody, Adam Starkey, Samuel G. Armato III
Author Affiliations +
Abstract
Rhinosinusitis is a sinonasal disease affecting 16% of the population. Volumetric segmentation can provide objective data that is useful when determining stage and therapeutic response. An automated volumetric segmentation method was developed and tested. Four patients underwent baseline and follow-up CT scans. For each patient, five sections were outlined by two otolaryngologists and the automated method. The median Dice coefficient between otolaryngologists was 0.74. The otolaryngologist and automated segmentations demonstrated acceptable agreement with a median Dice coefficient of 0.61. This automated method represents the first step in the creation of a computerized system for the quantitative 3D analysis of rhinosinusitis.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William F. Sensakovic, Jayant M. Pinto, Faud M. Baroody, Adam Starkey, and Samuel G. Armato III "Automated segmentation of mucosal change in rhinosinusitis patients", Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76243N (9 March 2010); https://doi.org/10.1117/12.844282
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Cited by 1 scholarly publication.
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KEYWORDS
Computed tomography

Image segmentation

Head

Computing systems

Analytical research

Inflammation

Bone

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