There is provided a method for generating a three-dimensional (3D) ultrasound image of a tissue volume using at least one processor, including: generating a series of two-dimensional (2D) ultrasound images of the tissue volume associated with a plurality of positions, respectively, along a scanning direction of the tissue volume； estimating, for each pair of consecutive 2D ultrasound images of the series of 2D ultrasound images, a distance between the positions associated with the pair of consecutive 2D ultrasound images based on a classification of a difference image generated from the pair of consecutive 2D ultrasound images using a deep neural network to produce a plurality of estimated distances associated with the plurality of pairs of consecutive 2D ultrasound images, respectively； modifying the number of 2D ultrasound images in the series of 2D ultrasound images based on the plurality of estimated distances to produce a modified series of 2D ultrasound images； and rendering the 3D ultrasound image of the tissue volume based on the modified series of 2D ultrasound images. There is also provided a corresponding system for generating a 3D ultrasound image of a tissue volume.
