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3D-2D Registration of Cerebral Angiograms: A Method and Evaluation on Clinical Images

机译:脑血管造影3D-2D配准:一种方法和对临床图像的评估

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摘要

Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established “gold standard” registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI.
机译:血管内图像引导干预(EIGI)涉及导管通过血管的导航,然后使用实时2D投影图像进行引导在异常部位进行治疗。在EIGI之前获取的3D图像用于量化血管异常并计划干预措施。如果与实时2D图像的信息融合在一起,它们还可以促进导航和处理。为此,需要3D-2D图像配准。尽管用于EIGI的几种3D-2D配准方法的配准精度低于1毫米,但是其临床应用仍然受到鲁棒性或可靠性不足的限制。在本文中,我们提出了一种基于3D脉管系统模型与实时2D图像强度梯度匹配的3D-2D配准方法。为了客观地验证3D-2D注册方法,我们获得了10名接受脑EIGI的患者的临床图像数据库,并通过在3D和2D图像中对齐基准标记建立了“黄金标准”注册。所提出的方法的平均套准精度低于0.65 mm,与经过测试的最新方法相当,执行时间不到1 s。凭借最高的成功注册率和最高的捕获范围,所提出的方法是最可靠的方法,因此是在EIGI中应用的良好候选者。

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