IEEE Trans Ultrason Ferroelectr Freq Control. 2021 Jun;68(6):2141-2149. doi: 10.1109/TUFFC.2021.3057540. Epub 2021 May 25.
Generation of super-resolution (SR) ultrasound (US) images, created from the successive localization of individual microbubbles in the circulation, has enabled the visualization of microvascular structure and flow at a level of detail that was not possible previously. Despite rapid progress, tradeoffs between spatial and temporal resolution may challenge the translation of this promising technology to the clinic. To temper these tradeoffs, we propose a method based on morphological image reconstruction. This method can extract from ultrafast contrast-enhanced US (CEUS) images hundreds of microbubble peaks per image (312-by-180 pixels) with intensity values varying by an order of magnitude. Specifically, it offers a fourfold increase in the number of peaks detected per frame, requires on the order of 100 ms for processing, and is robust to additive electronic noise (down to 3.6-dB CNR in CEUS images). By integrating this method to an SR framework, we demonstrate a sixfold improvement in spatial resolution, when compared with CEUS, in imaging chicken embryo microvessels. This method that is computationally efficient and, thus, scalable to large data sets may augment the abilities of SR-US in imaging microvascular structure and function.
从循环中单个微泡的连续定位生成的超分辨率 (SR) 超声 (US) 图像,使人们能够以前所未有的细节水平可视化微血管结构和血流。尽管取得了快速进展,但空间和时间分辨率之间的权衡可能会对该有前途的技术向临床的转化构成挑战。为了缓和这些权衡,我们提出了一种基于形态图像重建的方法。该方法可以从超快对比增强超声 (CEUS) 图像中提取每幅图像(312x180 像素)数百个微泡峰值,其强度值相差一个数量级。具体来说,它提供了每帧检测到的峰值数量的四倍增加,处理时间约为 100 毫秒,并且对附加电子噪声具有鲁棒性(在 CEUS 图像中低至 3.6-dB 的 CNR)。通过将该方法集成到 SR 框架中,我们在对鸡胚微血管成像时,与 CEUS 相比,空间分辨率提高了六倍。这种计算效率高且因此可扩展到大数据集的方法可能会增强 SR-US 成像微血管结构和功能的能力。