Monte Carlo-based simulation of virtual 3 and 4-dimensional cone-beam computed tomography from computed tomography images: An end-to-end framework and a deep learning-based speedup strategy

In radiotherapy, precise comparison of fan-beam computed tomography (CT) and cone-beam CT (CBCT) arises as a commonplace, yet intricate task. This paper proposes a publicly available end-to-end pipeline featuring an intrinsic deep-learning-based speedup technique for generating virtual 3D and 4D CBCT from CT images.