@article {11230,
	title = {Ultrasound-image-based cardiovascular tissue motion estimation.},
	journal = {IEEE Rev Biomed Eng},
	volume = {9},
	year = {2016},
	pages = {208-218},
	abstract = {The estimation of cardiovascular tissue motion from ultrasound images is a task of considerable importance but has remained difficult in clinical practice, mainly due to the limitations of ultrasound imaging and the complexity of tissue motion. This paper presents a survey of methodologies, along with physiologically relevant findings, regarding the estimation of motion of the myocardium and of central and peripheral arteries. Speckle tracking and modeling, and registration are the dominant methods used to calculate tissue displacements from sequences of images. Kinematic and mechanical indices are extracted from these displacements, which can provide valuable functional information about the cardiovascular system in normal and diseased conditions. An important application of motionbased strain indices involves the estimation of elastograms of the cardiovascular tissue. Motion analysis methods can be used to estimate a number of regional mechanical phenomena representing functional tissue properties, which are more sensitive to early changes due to ageing or disease. The importance of these methods lies in their potential to quantify in vivo tissue properties and to identify novel noninvasive personalized disease markers, toward early detection and optimal management of disease, along with increased patient safety. Their clinical usefulness remains to be demonstrated in larg trials.},
	url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=7458860},
	author = {Spyretta Golemati and Aimilia Gastounioti and Konstantina S. Nikita}
}
