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Abstract #4982

MIRTorch: A PyTorch-powered Differentiable Toolbox for Fast Image Reconstruction and Scan Protocol Optimization

Guanhua Wang1, Neel Shah2, Keyue Zhu2, Douglas C. Noll1, and Jeffrey A. Fessler2
1Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 2EECS, University of Michigan, Ann Arbor, MI, United States

Synopsis

MIRTorch (Michigan Image Reconstruction Toolbox for PyTorch) is an image reconstruction toolbox implemented with native Python/PyTorch. It provides fast iterative and data-driven image reconstruction on both CPUs and GPUs. Researchers can rapidly develop new model-based and learning-based methods (i.e., unrolled neural networks) with its convenient abstraction layers. With the full support of auto-differentiation, one may optimize imaging protocols, such as sampling patterns and image reconstruction parameters with gradient-based methods.

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