Fuzzy logic approach to extraction of intrathoracic airway trees from three-dimensional CT images

Wonkyu Park; Eric A. Hoffman; Milan Sonka

doi:10.1117/12.237925

16 April 1996 Fuzzy logic approach to extraction of intrathoracic airway trees from three-dimensional CT images

Wonkyu Park, Eric A. Hoffman, Milan Sonka

Proceedings Volume 2710, Medical Imaging 1996: Image Processing; (1996) https://doi.org/10.1117/12.237925
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

Accurate assessment of intrathoracic airway physiology requires sophisticated imaging and image segmentation of the three-dimensional airway tree structure. We have previously reported a rule-based method for three-dimensional airway tree segmentation from electron beam CT (EBCT) images. Here we report a new approach to airway tree segmentation in which fuzzy logic is used for image interpretation. In canine EBCT images, airways identified by the fuzzy logic method matched 276/337 observer-defined airways (81.9%) while the fuzzy method failed to detect the airways in the remaining 61 observer-determined locations (18.1%). By comparing the performance of the new fuzzy logic method and that of our former rule-based method, the fuzzy logic method significantly decreased the number of false airways (p less than 0.001).

Citation Download Citation

Wonkyu Park, Eric A. Hoffman, and Milan Sonka "Fuzzy logic approach to extraction of intrathoracic airway trees from three-dimensional CT images", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.237925

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