Single image super resolution on dynamic x-ray radiography based on a vision transformer

Hyunjong Kim; Ilwoong Choi; Dong Sik Kim; Choul Woo Shin

doi:10.1117/12.3006975

2 April 2024 Single image super resolution on dynamic x-ray radiography based on a vision transformer

Hyunjong Kim, Ilwoong Choi, Dong Sik Kim, Choul Woo Shin

Proceedings Volume 12926, Medical Imaging 2024: Image Processing; 1292631 (2024) https://doi.org/10.1117/12.3006975
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Single-image super resolution (SR) task has evolved mainly in natural imaging and achieved impressive performance by employing vision transformer-based methods. We can consider using these deep-learning-based SR methods to obtain high-resolution medical images to confirm the possibility of improving the resolution of radiography images. In this paper, we apply a vision transformer as a single-image SR method in dynamic X-ray radiography (DXR). Because utilizing high-resolution images in DXR is difficult due to the limitation of resources, applying a binning technique to downsize images is inevitable even though the technique degrades the image quality. However, the SR simulations show that the network model can restore the aliased signals and significantly improve the modulation transfer function from the downsized images. Therefore, using the SR method based on the vision transformer, we can effectively restore high-resolution images from downsized images and thus develop high-performance DXR systems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hyunjong Kim, Ilwoong Choi, Dong Sik Kim, and Choul Woo Shin "Single image super resolution on dynamic x-ray radiography based on a vision transformer", Proc. SPIE 12926, Medical Imaging 2024: Image Processing, 1292631 (2 April 2024); https://doi.org/10.1117/12.3006975

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