We demonstrated that at least two conditions are required for a fair comparison between deep neural networks for dipole inversion: First, test data need to have the same characteristics as training data. Second, hyperparameter tuning should be performed if training dataset is changed. Our study implies that a common dataset is necessary for a fair comparison of deep neural networks for QSM.
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