RadRotator: 3D Rotation of Radiographs with Diffusion Models

arXiv:2404.13000v1 Announce Type: cross
Abstract: Transforming two-dimensional (2D) images into three-dimensional (3D) volumes is a well-known yet challenging problem for the computer vision community. In the medical domain, a few previous studies attempted to convert two or more input radiographs into computed tomography (CT) volumes. Following their effort, we introduce a diffusion model-based technology that can rotate the anatomical content of any input radiograph in 3D space, potentially enabling the visualization of the entire anatomical content of the radiograph from …

abstract arxiv community computer computer vision cs.cv cs.lg diffusion diffusion models domain eess.iv images medical rotation studies three-dimensional type vision