System and method for 3d imaging reconstruction using dual-domain neural network

Abstract

This application describes a method and system for medical 3D imaging reconstruction based on limited-angle 2D image acquisition, which only requires 30˜50% of the data required by traditional scanner-based 3D reconstruction. This approach significantly reduces the radiation dose requirement and improves clinical efficiency. An example method includes: capturing a plurality of 2-dimensional (2D) projections of a target that cover a limited angle of the target; calibrating the plurality of 2D projections of the target to obtain a plurality of calibrated 2D projections; generating a sinogram based on the plurality of calibrated 2D projections; inputting the sinogram into a dual-domain neural network to obtain a 3D volumetric image of the target that is geometrically corrected and calibrated.