Abstract
A method for real-time localization of devices in fluoroscopic images is presented. Device pose is estimated using a Hough forest based detection framework. The method was applied to two types of devices used for transcatheter aortic valve replacement: a transesophageal echo (TEE) probe and prosthetic valve (PV). Validation was performed on clinical datasets, where both the TEE probe and PV were successfully detected in 95.8% and 90.1% of images, respectively. TEE probe position and orientation errors were 1.42 ± 0.79 mm and 2.59° ± 1.87°, while PV position and orientation errors were 1.04 ± 0.77 mm and 2.90° ± 2.37°. The Hough forest was implemented in CUDA C, and was able to generate device location hypotheses in less than 50 ms for all experiments.
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Hatt, C.R., Speidel, M.A., Raval, A.N. (2015). Hough Forests for Real-Time, Automatic Device Localization in Fluoroscopic Images: Application to TAVR. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9349. Springer, Cham. https://doi.org/10.1007/978-3-319-24553-9_38
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DOI: https://doi.org/10.1007/978-3-319-24553-9_38
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