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from Part III - Generative Models for Biomedical Imaging
Published online by Cambridge University Press: 15 September 2023
In this chapter, we provide an overview of a recent image-reconstruction method that uses a deep generative algorithm for dynamic magnetic resonance-imaging (dMRI). We begin by briefly introducing the imaging modality of dMRI, the associated image-reconstruction problem, and existing reconstruction approaches. Next, we introduce the time-dependent deep image prior (TD-DIP), which exploits the structure of convolutional neural networks (CNNs) as a regularizing prior. We show some representative results and discuss the pros and cons of this regularizing paradigm. Finally, we discuss a few potential remaining limitations.
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