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Abstract #3976

Necessity for a common dataset for a fair comparison between deep neural networks for QSM

Chungseok Oh1, Woojin Jung1, Hwihun Jeong1, and Jongho Lee1
1Seoul National University, Seoul, Korea, Republic of

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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