MERLIN: In-depth investigation on complex-valued image reconstruction in PyTorch and Tensorflow

Machine learning (ML) has become a powerful technique for reconstructing undersampled MRI. However, applying ML to MRI reconstruction requires several essential building blocks, consisting of general operations and MRI-specific operators in the context of reconstruction. While the former are available in generic frameworks such as Keras/TensorFlow or PyTorch, the MR-specific operators are generally custom-implemented. MERLIN was proposed as a generic toolkit for ML-based medical imaging to harmonize the machine learning landscape and to provide complex-valued interfaces for commonly used back-ends. Here, we evaluate MERLIN as a cross-platform toolkit for complex-valued image reconstruction.