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29 March 2013 3D segmentation and reconstruction of endobronchial ultrasound
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Abstract
State-of-the-art practice for lung-cancer staging bronchoscopy often draws upon a combination of endobronchial ultrasound (EBUS) and multidetector computed-tomography (MDCT) imaging. While EBUS offers real-time in vivo imaging of suspicious lesions and lymph nodes, its low signal-to-noise ratio and tendency to exhibit missing region-of-interest (ROI) boundaries complicate diagnostic tasks. Furthermore, past efforts did not incorporate automated analysis of EBUS images and a subsequent fusion of the EBUS and MDCT data. To address these issues, we propose near real-time automated methods for three-dimensional (3D) EBUS segmentation and reconstruction that generate a 3D ROI model along with ROI measurements. Results derived from phantom data and lung-cancer patients show the promise of the methods. In addition, we present a preliminary image-guided intervention (IGI) system example, whereby EBUS imagery is registered to a patient’s MDCT chest scan.
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Xiaonan Zang, Mikhail Breslav, and William E. Higgins "3D segmentation and reconstruction of endobronchial ultrasound", Proc. SPIE 8675, Medical Imaging 2013: Ultrasonic Imaging, Tomography, and Therapy, 867505 (29 March 2013); https://doi.org/10.1117/12.2004901
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