Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, Saint Petersburg, Russia.
Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA.
Int J Comput Assist Radiol Surg. 2019 Apr;14(4):577-586. doi: 10.1007/s11548-019-01926-0. Epub 2019 Feb 23.
The goal of this study was to develop an algorithm that enhances the temporal resolution of two-dimensional color Doppler echocardiography (2D CDE) by reordering all the acquired frames and filtering out the frames corrupted by out-of-plane motion and arrhythmia.
The algorithm splits original frame sequence into the fragments based on the correlation with a reference frame. Then, the fragments are aligned temporally and merged into a resulting sequence that has higher temporal resolution. We evaluated the algorithm with 10 animal epicardial 2D CDE datasets of the right ventricle and compared it with the existing approaches in terms of resulting frame rate, image stability and execution time.
We identified the optimal combination of alternatives for each step, which resulted in an increase in frame rate from 14 ± 0.87 to 238 ± 93 Hz. The average execution time was 7.23 ± 0.48 s in comparison with 0.009 ± 0.001 s for ECG gating and 1167.37 ± 587.85 s for flow reordering. Our approach demonstrated a significant (p < 0.01) increase in image stability compared with ECG gating and flow reordering.
This work presents an offline algorithm for temporal enhancement of 2D CDE. Unlike previous frame reordering approaches, it can filter out-of-plane or corrupted frames, increasing the quality of the results, which substantially increases diagnostic value of 2D CDE. It can be used for high-frame-rate intraoperative imaging of intraventricular and valve regurgitant flows and is potentially modifiable for real-time use on ultrasound machines.
本研究旨在开发一种算法,通过重新排序所有获取的帧并滤除平面外运动和心律失常引起的帧,来提高二维彩色多普勒超声心动图(2D CDE)的时间分辨率。
该算法基于与参考帧的相关性将原始帧序列分割成片段。然后,这些片段在时间上对齐并合并成一个具有更高时间分辨率的结果序列。我们使用 10 个动物心外膜 2D CDE 右心室数据集评估了该算法,并在帧率、图像稳定性和执行时间方面与现有方法进行了比较。
我们确定了每个步骤的最佳替代方案组合,从而将帧率从 14±0.87 增加到 238±93 Hz。与 ECG 门控的平均执行时间 7.23±0.48 s 相比,与流量重新排序的平均执行时间 0.009±0.001 s 相比,平均执行时间显著增加(p<0.01)。与 ECG 门控和流量重新排序相比,我们的方法显著提高了图像稳定性(p<0.01)。
本研究提出了一种用于增强二维彩色多普勒超声心动图时间分辨率的离线算法。与以前的帧重新排序方法不同,它可以滤除平面外或损坏的帧,提高结果的质量,从而大大提高二维彩色多普勒超声心动图的诊断价值。它可用于心室内和瓣膜反流流量的高帧率术中成像,并且具有潜在的可修改性,可用于超声设备的实时使用。