Angle-Independent Tissue Velocity Measurement

Angle-Independent Tissue Velocity Measurement via Adaptive Decomposition Clutter Filtering and Speckle Tracking
Caterina Gallippi

Ultrasonic imaging has been employed to assess the velocity of underlying tissue structures for decades. At the onset of the application, the shift in Doppler frequency in continuous wave (CW) systems was related to tissue displacement over time, but depth information, and hence localization of velocity, was ambiguous. As Doppler technology advanced to pulsed wave (PW) systems for depth localization, the inherent angle-dependence of conventional Doppler methods still restricted velocity estimation to the axial dimension only. Several methods for overcoming the angle-dependence of Doppler methods have been presented in literature, each with specific advantages and disadvantages. The goal of this research is to investigate Speckle Tracking as a method for angle-independent vector flow imaging. Although motion tracking in ultrasound has applications in many areas, including cardiac, angiogenesis, remote palpation and elastography imaging, this research focus on the application of blood velocity imaging in the human peripheral vascular system. Intrinsic to ultrasonic blood velocity estimation feasibility is sufficient removal of the vessel wall signal which overbears the blood signal for velocity measurement. As such, this research also focuses on a method for adaptive clutter rejection with application to tissue motion tracking in ultrasound. See below an example colorflow image of lateral blood flow in the human common carotid artery derived from adaptive decomposition filtering and Speckle Tracking methods. The associate color scale is also shown.

Duke University
Department of Biomedical Engineering

Ultrasonic imaging has been employed to assess the velocity of underlying tissue structures for decades. At the onset of the application, the shift in Doppler frequency in continuous wave (CW) systems was related to tissue displacement over time, but depth information, and hence localization of velocity, was ambiguous. As Doppler technology advanced to pulsed wave (PW) systems for depth localization, the inherent angle-dependence of conventional Doppler methods still restricted velocity estimation to the axial dimension only. Several methods for overcoming the angle-dependence of Doppler methods have been presented in literature, each with specific advantages and disadvantages. The goal of this research is to investigate Speckle Tracking as a method for angle-independent vector flow imaging. Although motion tracking in ultrasound has applications in many areas, including cardiac, angiogenesis, remote palpation and elastography imaging, this research focus on the application of blood velocity imaging in the human peripheral vascular system. Intrinsic to ultrasonic blood velocity estimation feasibility is sufficient removal of the vessel wall signal which overbears the blood signal for velocity measurement. As such, this research also focuses on a method for adaptive clutter rejection with application to tissue motion tracking in ultrasound. See below an example colorflow image of lateral blood flow in the human common carotid artery derived from adaptive decomposition filtering and Speckle Tracking methods. The associate color scale is also shown.