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Abstract #4045

Sinogram Transformers: Accelerating Radial MRI using Vision Transformers

David Parra1, Phillip Martin2, Maria Altbach3,4, and Ali Bilgin2,3,4,5
1Computer Science, University of Arizona, Tucson, AZ, United States, 2Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States, 3Biomedical Engineering, University of Arizona, Tucson, AZ, United States, 4Medical Imaging, University of Arizona, Tucson, AZ, United States, 5Applied Mathematics, University of Arizona, Tucson, AZ, United States

Synopsis

The aim of this work is to investigate the used of Transformer architectures in radial image reconstruction. While most deep-learning image reconstruction methods are based on convolutional neural networks (CNNs), recent advances in computer vision suggest that Transformer architecture may provide a favorable alternative in many vision tasks. In this work, we demonstrate that Transformer architectures can be used for sinogram interpolation and yield results comparable to CNNs.

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Keywords