Careful optimization of the full imaging pipeline, from data acquisition to post-processing, is a crucial part of any magnetic resonance imaging study. However, testing and optimization of pipelines in the “real world” is expensive and challenging, and hence simulations play a key role in the process. In this chapter, we discuss simulation frameworks and the ways they can be applied to optimize imaging pipelines. We cover examples of the use of simulation to evaluate post-processing algorithms, study imaging artifacts, design and test new acquisition techniques, and to produce data for training machine-learning based post-processing tools.
|Title of host publication||Biomedical Image Synthesis and Simulation|
|Subtitle of host publication||Methods and Applications|
|Number of pages||29|
|Publication status||Published - 1 Jan 2022|
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