A computer-implemented method for obtaining a composite 3D ultrasound image of a region of interest, the method comprising: obtaining preliminary ultrasound data from a region of interest of a subj ect; identifying an anatomical feature within the region of interest based on the preliminary ultrasound data; determining a first imaging position and one or more additional imaging positions based on the anatomical feature; obtaining a first 3D ultrasound image from the first imaging position and one or more additional 3D ultrasound images from the one ore more additional imaging positions, wherein a portion of the first 3D ultrasound image overlaps a portion of the one or more additional 3D ultrasound images, thereby forming an overlapping portion and wherein the overlapping portion comprises the anatomical feature; performing spatial registration between the first 3D ultrasound image and the one or more additional 3D ultrasound images based on the anatomical feature, wherein performing spatial registration comprises: generating a 3D point cloud within the first 3D ultrasound image and the one or more additional 3D ultrasound images, wherein the 3D point cloud represents a surface within the first 3D ultrasound image and a surface within the one or more additional 3D ultrasound images; and generating a probability map based on the 3D point cloud, the probability map representing a confidence value of the anatomical feature occupying a given point within the first 3D ultrasound image and the one or more additional 3D ultrasound images; and blending the first 3D ultrasound image and the one or more additional 3D ultrasound images based on the spatial registration, thereby generating a composite 3D ultrasound image, wherein blending the first 3D ultrasound image and the one or more additional 3D ultrasound images is based on the probability map. obtaining preliminary ultrasound data from a region of interest of a subj ect; identifying an anatomical feature within the region of interest based on the preliminary ultrasound data; determining a first imaging position and one or more additional imaging positions based on the anatomical feature; obtaining a first 3D ultrasound image from the first imaging position and one or more additional 3D ultrasound images from the one ore more additional imaging positions, wherein a portion of the first 3D ultrasound image overlaps a portion of the one or more additional 3D ultrasound images, thereby forming an overlapping portion and wherein the overlapping portion comprises the anatomical feature; performing spatial registration between the first 3D ultrasound image and the one or more additional 3D ultrasound images based on the anatomical feature, wherein performing spatial registration comprises: generating a 3D point cloud within the first 3D ultrasound image and the one or more additional 3D ultrasound images, wherein the 3D point cloud represents a surface within the first 3D ultrasound image and a surface within the one or more additional 3D ultrasound images; and generating a probability map based on the 3D point cloud, the probability map representing a confidence value of the anatomical feature occupying a given point within the first 3D ultrasound image and the one or more additional 3D ultrasound images; and generating a 3D point cloud within the first 3D ultrasound image and the one or more additional 3D ultrasound images, wherein the 3D point cloud represents a surface within the first 3D ultrasound image and a surface within the one or more additional 3D ultrasound images; and generating a probability map based on the 3D point cloud, the probability map representing a confidence value of the anatomical feature occupying a given point within the first 3D ultrasound image and the one or more additional 3D ultrasound images; and blending the first 3D ultrasound image and the one or more additional 3D ultrasound images based on the spatial registration, thereby generating a composite 3D ultrasound image, wherein blending the first 3D ultrasound image and the one or more additional 3D ultrasound images is based on the probability map.