Haouchine Nazim, Juvekar Parikshit, Xiong Xin, Luo Jie, Kapur Tina, Du Rose, Golby Alexandra, Frisken Sarah
Harvard Medical Shcool, Boston, MA, USA.
Brigham and Women's Hospital, Boston, MA, USA.
Med Image Comput Comput Assist Interv. 2021 Sep-Oct;12906:171-180. doi: 10.1007/978-3-030-87231-1_17. Epub 2021 Sep 21.
Digital Subtraction Angiography (DSA) provides high resolution image sequences of blood flow through arteries and veins and is considered the gold standard for visualizing cerebrovascular anatomy for neurovascular interventions. However, acquisition frame rates are typically limited to 1-3 fps to reduce radiation exposure, and thus DSA sequences often suffer from stroboscopic effects. We present the first approach that permits generating high frame rate DSA sequences from low frame rate acquisitions eliminating these artifacts without increasing the patient's exposure to radiation. Our approach synthesizes new intermediate frames using a phase-aware Convolutional Neural Network. This network accounts for the non-linear blood flow progression due to vessel geometry and initial velocity of the contrast agent. Our approach out-performs existing methods and was tested on several low frame rate DSA sequences of the human brain resulting in sequences of up to 17 fps with smooth and continuous contrast flow, free of flickering artifacts.
数字减影血管造影(DSA)可提供动脉和静脉血流的高分辨率图像序列,被认为是用于神经血管介入手术的脑血管解剖结构可视化的金标准。然而,为了减少辐射暴露,采集帧率通常限制在1-3帧/秒,因此DSA序列经常受到频闪效应的影响。我们提出了第一种方法,该方法允许从低帧率采集生成高帧率DSA序列,在不增加患者辐射暴露的情况下消除这些伪影。我们的方法使用相位感知卷积神经网络合成新的中间帧。该网络考虑了由于血管几何形状和造影剂初始速度导致的非线性血流进展。我们的方法优于现有方法,并在几个人脑低帧率DSA序列上进行了测试,得到了高达17帧/秒的序列,具有平滑连续的造影剂流动,没有闪烁伪影。