9 March 2017 Automated 3D coronary sinus catheter detection using a scanning-beam digital x-ray system
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Abstract
Scanning-beam digital x-ray (SBDX) is an inverse geometry x-ray fluoroscopy system capable of tomosynthesis-based 3D tracking of catheter electrodes concurrent with fluoroscopic display. To facilitate respiratory motion-compensated 3D catheter tracking, an automated coronary sinus (CS) catheter detection algorithm for SBDX was developed. The technique uses the 3D localization capability of SBDX and prior knowledge of the catheter shape. Candidate groups of points representing the CS catheter are obtained from a 3D shape-constrained search. A cost function is then minimized over the groups to select the most probable CS catheter candidate. The algorithm was implemented in MATLAB and tested offline using recorded image sequences of a chest phantom containing a CS catheter, ablation catheter, and fiducial clutter. Fiducial placement was varied to create challenging detection scenarios. Table panning and elevation was used to simulate motion. The CS catheter detection method had 98.1% true positive rate and 100% true negative rate in 2755 frames of imaging. Average processing time was 12.7 ms/frame on a PC with a 3.4 GHz CPU and 8 GB memory. Motion compensation based on 3D CS catheter tracking was demonstrated in a moving chest phantom with a fixed CS catheter and an ablation catheter pulled along a fixed trajectory. The RMS error in the tracked ablation catheter trajectory was 1.41 mm, versus 10.35 mm without motion compensation. A computationally efficient method of automated 3D CS catheter detection has been developed to assist with motion-compensated 3D catheter tracking and registration of 3D cardiac models to tracked catheters.
Conference Presentation
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David A. P. Dunkerley, Jordan M. Slagowski, Lindsay E. Bodart, Michael A. Speidel, "Automated 3D coronary sinus catheter detection using a scanning-beam digital x-ray system", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101321N (9 March 2017); doi: 10.1117/12.2254443; https://doi.org/10.1117/12.2254443
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