Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial IntelligenceThis work investigates the impact of model degeneracy on machine learning-based tissue microstructure estimation. While there have been several empirical reports suggesting machine learning can not resolve model degeneracy, the impact of model degeneracy is poorly understood. Here we show how model degeneracy can be categorised into three types with varying degrees of impact on machine learning-based microstructure estimation. Our finding is important for designing optimal training data distribution.
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