Deformable Registration of Coronary Arteries with Topological Constraints for Image-Guided Vascular Interventions.

Abstract

2D/3D registration of preoperative computed tomography angiography with intra-operative X-ray angiography improves image guidance in percutaneous coronary intervention. However, previous registration methods are inaccurate and time-consuming due to simple deformation and iterative optimization, respectively. In this paper, we propose a novel method for non-rigid registration of coronary arteries based on a point set registration network, which predicts the complex deformation field directly without iterative optimization. In order to maintain the structure of coronary arteries, we advance the classical point set registration network with a loss function containing global and local topological constraints. The method was evaluated on ten clinical data, and it achieved a median chamfer distance of 73.60 pixels with a run time of less than 1s on CPU. Experimental results demonstrate that the proposed method is highly accurate and efficient.