Connecting physics and deep learning to generalize medical image analysis tasks
Abstract: Magnetic Resonance Imaging (MRI) can have multiple flavours: T1, T2, proton density, fMRI, diffusion MRI, etc. These socalled Quantitative MRI techniques are useful for monitoring pathologies such as multiple sclerosis and Alzheimer s disease. However, quantitative MRI data require complex analysis pipelines that are often executed manually and hence suffer from poor reproducibility. Deep learning (DL) appears to be an ideal candidate to help automatize certain analysis tasks. Unfortunately, wh
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