GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention

Ashish Sinha; Yohei Sugawara; Yuichiro Hirano

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arXiv · 1909.12525

GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention

Ashish Sinha·Yohei Sugawara·Yuichiro Hirano

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Abstract

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.

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eess.IV cs.CV cs.LG

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BibTeX RIS

Ashish Sinha, Yohei Sugawara, Yuichiro Hirano. 2019-09-27. GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention. https://arxiv.org/abs/1909.12525

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