用心脏收缩与舒张期影像生成动态4D冠状动脉树
4D-CAT: Synthesis of 4D Coronary Artery Trees from Systole and Diastole
- 通过中心线预测形变场，实现心缩期到心舒期的映射
- 基于形变场插值生成完整心动周期的血管动态
- 适用于低剂量造影剂下冠脉动态建模，临床价值高
从CT图像重建的三维血管模型广泛用于医学诊断。由于心脏搏动导致血管变形，不同相位的血管影像状态差异可能引发误诊。4D模型可模拟完整心动周期。由于患者造影剂注射剂量受限，仅能获取有限相位影像，因此通过少量相位影像合成4D冠状动脉树具有重要价值。本文提出一种4D冠状动脉树生成方法：通过预测心缩期到心舒期的形变场，在时间线上进行插值，获得点的运动轨迹。具体地，以中心线表示血管，采用基于立方体排序与神经网络的方法推断形变场；根据中心线点的形变场，聚合并插值邻近血管点，得到各相位的位移向量。实验验证了该方法在非刚性血管点配准和4D冠状动脉树生成上的有效性。
原文摘要 · Abstract (English)
The three-dimensional vascular model reconstructed from CT images is widely used in medical diagnosis. At different phases, the beating of the heart can cause deformation of vessels, resulting in different vascular imaging states and false positive diagnostic results. The 4D model can simulate a complete cardiac cycle. Due to the dose limitation of contrast agent injection in patients, it is valuable to synthesize a 4D coronary artery trees through finite phases imaging. In this paper, we propose a method for generating a 4D coronary artery trees, which maps the systole to the diastole through deformation field prediction, interpolates on the timeline, and the motion trajectory of points are obtained. Specifically, the centerline is used to represent vessels and to infer deformation fields using cube-based sorting and neural networks. Adjacent vessel points are aggregated and interpolated based on the deformation field of the centerline point to obtain displacement vectors of different phases. Finally, the proposed method is validated through experiments to achieve the registration of non-rigid vascular points and the generation of 4D coronary trees.
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