  This work investigates the use of guided attention in the reconstruction of
CTvolumes from biplanar DRRs. We try to improve the visual image quality of the
CT reconstruction using Guided Attention based GANs (GA-GAN). We also consider
the use of Vector Quantization (VQ) for the CT reconstruction so that the
memory usage can be reduced, maintaining the same visual image quality. To the
best of our knowledge no work has been done before that explores the Vector
Quantization for this purpose. Although our findings show that our approaches
outperform the previous works, still there is a lot of room for improvement.
