Synopsis

Keywords: Image acquisition: Modelling

Model-based fitting is a powerful technique for extracting quantitative information from MRI data. We will discuss the challenges associated with model-based fitting, including model selection, noise and artifacts, parameter estimation, validation and reproducibility, and computation time.

Model-based fitting is a powerful technique for extracting quantitative information from MRI data. This talk will provide an overview of the basic principles and methods of model-based fitting, with a particular focus on its applications in myelin water imaging. We will discuss the challenges associated with model-based fitting, including model selection, noise and artifacts, parameter estimation, validation and reproducibility, and computation time. We will also review strategies for addressing these challenges, such as regularization, constraining parameter values, and model selection techniques. The talk will conclude with a discussion of future directions for model-based fitting in MRI and its potential impact on clinical practice.

Acknowledgements

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References

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