Temporal patterns of cardiac motion provide important information for cardiac disease diagnosis. This pattern could be obtained by three-directional CINE multi-slice left ventricular myocardial velocity mapping (3Dir MVM), which is a cardiac MR technique providing magnitude and phase information of the myocardial motion simultaneously. However, long acquisition time limits the usage of this technique by causing breathing artifacts, while shortening the time causes low temporal resolution and may provide an inaccurate assessment of cardiac motion. In this study, we proposed a frame synthesis algorithm to increase the temporal resolution of 3Dir MVM data. Our algorithm is featured by 1) three attention-based encoders which accept magnitude images, phase images, and myocardium segmentation masks respectively as inputs; 2) three decoders that output the interpolated frames and corresponding myocardium segmentation results; and 3) loss functions highlighting myocardium pixels. Our algorithm can not only increase the temporal resolution 3Dir MVMs, but can also generates the myocardium segmentation results at the same time.
翻译:心脏运动的时空模式为心脏疾病诊断提供了重要信息。 这种模式可以通过三方向的 CINE 多切左心心肌速度映射(3Dir MVM)获得,这是一种心脏MR技术,同时提供心心肌运动的大小和阶段信息。然而,长期获取时间限制这种技术的使用,方法是制造呼吸器,同时缩短时间,造成低时间分辨率,并可能提供对心脏运动的不准确评估。在这项研究中,我们提出了一个框架合成算法,以提高3Dir MVM数据的时间分辨率。我们的算法有1个基于关注的编码器,分别接受大小图像、相片图像和心肌分解面罩作为输入;2) 3个导出中间框架和相应的心肌分裂结果的解剖器;3) 突出心肌素像素的损失函数。我们的算法不仅可以增加时间分辨率3Dir MVMS,而且还可以同时产生心肌分解结果。