Abstract: Described herein are calibration jigs and methods used to design and fabricate calibration jigs as well as associated workflows that may be used for determining the calibration parameters used to create a 2D image of a 3D scene, wherein the calibration jig has the shape of an isosceles right semi-triangular prism and is configured to ergonomically fit an anterior-medial tibial position on a patient's leg.

Abstract: A computer-implemented method of using a neural network to reconstruct three dimensional (3D) images of an anatomical structure from two-dimensional (2D) images including the steps of: (a) in a 3D image training dataset associated with the anatomical structure to be reconstructed, creating respective 3D ground truth masks and/or heat maps for each 3D training image; (b) obtaining 2D images of the anatomical structure and their associated calibration parameters; (c) generating a 3D volume including a 3D array of voxels and a plurality of channels, at least some of the channels associated with the one or more generated 2D images and associated calibration parameters of step (b); and (d) training a neural network by associating the 3D ground truth masks and/or heat maps with the generated 3D volume.