| abstract |
There is provided a method of training a neural network for reconstructing of a 3D point cloud from 2D image(s), comprising: extracting (104) point clouds each represented by an ordered list of coordinates, from 3D anatomical images depicting a target anatomical structure, selecting (106) one of the plurality of point clouds as a template, non-rigidly registering the template with each of the point clouds to compute (108) a respective warped template having a shape of the respective point cloud and retaining the coordinate order of the template, wherein the warped templates are consistent in terms of coordinate order, receiving (110) 2D anatomical images depicting the target anatomical structure depicted in corresponding 3D anatomical images, and training (114) a neural network, according to a training dataset of the warped templates and corresponding 2D images, for mapping 2D anatomical image(s) into a 3D point cloud. |