Paper
24 June 1998 Automatic detection of endobronchial lesions using virtual bronchoscopy: comparison of two methods
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Abstract
3D reconstruction of medical images is increasingly being used to diagnose disease and to direct therapy. Virtual bronchoscopy is a recently developed type of 3D reconstruction of the airways that may be useful for diagnosis of lesions of the airway. In this study, we compare two methods for computer-aided diagnosis of polypoid airway tumors: a parametric (`patch') and non-parametric ('grey-scale') algorithm. We found that both methods have comparable specificities. Although the non-parametric method is twelve times faster than the parametric method, we found that is sensitivity lags behind that of the parametric method by 3 to 16% when lesions of all sizes are considered. For lesions at least 5 mm in size, the sensitivities are comparable if a small convolution kernel is used.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ronald M. Summers, Lynne M. Pusanik, and James D. Malley "Automatic detection of endobronchial lesions using virtual bronchoscopy: comparison of two methods", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310909
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Cited by 15 scholarly publications.
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KEYWORDS
Bronchoscopy

Computed tomography

3D image processing

Convolution

3D modeling

Computer aided diagnosis and therapy

Detection and tracking algorithms

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