Bakas Spyridon, Doulgerakis-Kontoudis Matthaios, Hunter Gordon J A, Sidhu Paul S, Makris Dimitrios, Chatzimichail Katerina
Digital Information Research Centre (DIRC), School of Computer Science & Mathematics, Faculty of Science, Engineering and Computing (SEC), Kingston University, London, United Kingdom; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, University of Pennsylvania, Richards Medical Research Laboratories, Hamilton Walk, Philadelphia, Pennsylvania, USA.
Digital Information Research Centre (DIRC), School of Computer Science & Mathematics, Faculty of Science, Engineering and Computing (SEC), Kingston University, London, United Kingdom; Medical Imaging and Image Interpretation Group, School of Computer Science, University of Birmingham, Edgbaston, United Kingdom.
Ultrasound Med Biol. 2019 Jun;45(6):1380-1396. doi: 10.1016/j.ultrasmedbio.2019.01.023. Epub 2019 Apr 2.
This study investigates the application and evaluation of existing indirect methods, namely point-based registration techniques, for the estimation and compensation of observed motion included in the 2-D image plane of contrast-enhanced ultrasound (CEUS) cine-loops recorded for the characterization and diagnosis of focal liver lesions (FLLs). The value of applying motion compensation in the challenging modality of CEUS is to assist in the quantification of the perfusion dynamics of an FLL in relation to its parenchyma, allowing for a potentially accurate diagnostic suggestion. Towards this end, this study also proposes a novel quantitative multi-level framework for evaluating the quantification of FLLs, which to the best of our knowledge remains undefined, notwithstanding many relevant studies. Following quantitative evaluation of 19 indirect algorithms and configurations, while also considering the requirement for computational efficiency, our results suggest that the "compact and real-time descriptor" (CARD) is the optimal indirect motion compensation method in CEUS.
本研究调查了现有间接方法，即基于点的配准技术，在估计和补偿用于局灶性肝病变（FLL）特征化和诊断的对比增强超声（CEUS）电影环二维图像平面中所观察到的运动方面的应用和评估。在具有挑战性的CEUS模态中应用运动补偿的价值在于辅助量化FLL与其实质相关的灌注动力学，从而得出潜在准确的诊断建议。为此，本研究还提出了一个用于评估FLL量化的新颖定量多层次框架，据我们所知，尽管有许多相关研究，但该框架仍未定义。在对19种间接算法和配置进行定量评估时，同时考虑计算效率的要求，我们的结果表明，“紧凑实时描述符”（CARD）是CEUS中最佳的间接运动补偿方法。
