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q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans
[chapter]
2015
Lecture Notes in Computer Science
Diffusion MRI uses a multi-step data processing pipeline. With certain steps being prone to instabilities, the pipeline relies on considerable amounts of partly redundant input data, which requires long acquisition time. This leads to high scan costs and makes advanced diffusion models such as diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) inapplicable for children and adults who are uncooperative, uncomfortable or unwell. We demonstrate how deep
doi:10.1007/978-3-319-24553-9_5
fatcat:q6k5nzqnkrgptge3dykmg72mfe