Method for shear wave elasticity imaging comprising the following steps:
a) acquiring B-mode ultrasound images of a target region in a body under examination;
b) selecting a region of interest inside the said B-mode image;
c) transmitting a shear wave excitation pulse focalized on an excitation region;
d) measuring the displacements of a certain number of tracking focal points or depth ranges at different depths positions along each one of a predefined number of laterally staggered tracking lines within the selected region of interest;
e) determining a curve representing the displacement of the tissue as a function of time at different spatial locations within the region of interest;
f) determining for each said spatial locations in the region of interest the time of arrival of the shear wave at the said spatial location by setting as the time of arrival of the shear wave as a function of the curve representing the displacement of the tissue as a function of time; g) finding the linear functional relation between the time of arrival and the spatial coordinate in the said lateral direction, i.e. in the direction of propagation of the shear wave perpendicular to the direction of the tracking lines, which linear function best approximates the determined time of arrivals at the positions of the tracking lines along the said lateral direction;
h) determining the inverse of the velocity of the shear wave in a spatial location as the angular coefficient of the said linear function in a coordinate system representing the time of arrival along the y-coordinate and the position along the lateral direction at which the time of arrival has been recorded on the x-coordinate, i.e. the slope of the straight line representing the said linear function in the said coordinate system,
and which method further comprises the following steps:
i) step f) is carried out by considering as time of arrivals the time related to each local maxima of the displacement curve at the corresponding spatial location, and
j) step g) is carried out by determining the linear function best fitting the said data pairs of local maxima of the displacement and related time of arrival applying a Random Sample Consensus algorithm (RANSAC algorithm).