Generation of synthetic tomographic images from biplanar X-ray: a narrative review of history, methods, and the state of the art.

This narrative review presents deep learning-based strategies for generating synthetic 3D CT-like images from biplanar or multiplanar 2D X-ray data. Current limitations of conventional CT imaging are discussed, hence emphasizing the potential of synthetic CT reconstruction as an alternative technique in certain scenarios. Previous non deep learning approaches for 3D reconstruction from 2D X-rays are presented, indicating their weaknesses and thus pointing out the potential benefits of deep learning techniques.