An improved neural network infers spatially adaptive sparsity level maps for convolutional dictionaries, enabling filter-permutation invariance and dictionary changes at inference while showing reduced degradation on out-of-distribution low-field MRI data.
More precisely, during training, we first compute sT ′ = FISTAT ′ (s0,A,D,y ′,Λ)with the FISTA-block with the current estimate ofΛwithouttracking gradients
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Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries
An improved neural network infers spatially adaptive sparsity level maps for convolutional dictionaries, enabling filter-permutation invariance and dictionary changes at inference while showing reduced degradation on out-of-distribution low-field MRI data.