International Journal of Pattern Recognition and Artificial Intelligence
Dual-View X-ray to 3D CT Reconstruction via Discrete Latent Translation with VQ-VAE and Transformer
Three-dimensional (3D) CT reconstruction from dual-view X-ray data is a severely ill-posed inverse problem, due to the substantial loss of structural information caused by the sparsity of the projection data. To address this challenge, we propose a dual-view X-ray-to-CT reconstruction framework based on vector quantized variational autoencoders (VQ-VAEs) and Transformer-based latent code translation. Specifically, a 3D VQ-VAE model is pre-trained to learn discrete latent representations of CT volumes, while a 2D VQ …