S Miao1, A Tuysuzoglu2, Z J Wang3, R Liao2. 1. Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, 08540, USA. shun.miao@siemens.com. 2. Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, 08540, USA. 3. Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Abstract
PURPOSE: Real-time 6 degrees of freedom (6DoF) pose recovery and tracking from X-ray images is a key enabling technology for many interventional imaging applications. However, real-time 2D/3D registration is a very challenging problem because of the heavy computation in iterative digitally reconstructed radiograph (DRR) generation. In this paper, we propose a real-time 2D/3D registration framework using library-based DRRs to achieve high computational efficiency. METHOD: The proposed method pre-computes a library of canonical DRRs and reconstructs library-based DRRs (libDRRs) during registration without online rendering. The transformation parameters are decoupled to 2 geometry-relevant and 4 geometry-irrelevant ones so that canonical DRRs only need to cover the variation of 2 geometry-relevant parameters, making it practical to be pre-computed and stored. The 2D/3D registration using libDRRs is then solved as a hybrid optimization problem, i.e., continuous in geometry-irrelevant parameters while discrete in geometry-relevant parameters. RESULTS: On 5 fluoroscopic sequences with 246 frames acquired during animal studies with a transesophageal echocardiography (TEE) probe in the field of view, 6DoF tracking of the TEE probe using the proposed method achieved a mean target registration error in the projection direction (mTREproj) of 0.81 mm, a success rate of 100 % (defined as mTREproj [Formula: see text]2.5 mm), and a registration frame rate of 23.1 fps on a pure CPU-based implementation executed in a single thread. CONCLUSION: Using libDRRs with a hybrid optimization can significantly improve the computational efficiency (up to tenfold) for 6DoF pose recovery and tracking with little degradation in robustness and accuracy, compared to conventional intensity-based 2D/3D registration using ray casting DRRs with a continuous optimization.
PURPOSE: Real-time 6 degrees of freedom (6DoF) pose recovery and tracking from X-ray images is a key enabling technology for many interventional imaging applications. However, real-time 2D/3D registration is a very challenging problem because of the heavy computation in iterative digitally reconstructed radiograph (DRR) generation. In this paper, we propose a real-time 2D/3D registration framework using library-based DRRs to achieve high computational efficiency. METHOD: The proposed method pre-computes a library of canonical DRRs and reconstructs library-based DRRs (libDRRs) during registration without online rendering. The transformation parameters are decoupled to 2 geometry-relevant and 4 geometry-irrelevant ones so that canonical DRRs only need to cover the variation of 2 geometry-relevant parameters, making it practical to be pre-computed and stored. The 2D/3D registration using libDRRs is then solved as a hybrid optimization problem, i.e., continuous in geometry-irrelevant parameters while discrete in geometry-relevant parameters. RESULTS: On 5 fluoroscopic sequences with 246 frames acquired during animal studies with a transesophageal echocardiography (TEE) probe in the field of view, 6DoF tracking of the TEE probe using the proposed method achieved a mean target registration error in the projection direction (mTREproj) of 0.81 mm, a success rate of 100 % (defined as mTREproj [Formula: see text]2.5 mm), and a registration frame rate of 23.1 fps on a pure CPU-based implementation executed in a single thread. CONCLUSION: Using libDRRs with a hybrid optimization can significantly improve the computational efficiency (up to tenfold) for 6DoF pose recovery and tracking with little degradation in robustness and accuracy, compared to conventional intensity-based 2D/3D registration using ray casting DRRs with a continuous optimization.
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