Quantification of MR spectra by deep learning in an idealized setting: Investigation of forms of input, network architectures, optimization by ensembles of networks, and training bias
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DOI: 10.1002/mrm.29561
Abstract: The aims of this work are (1) to explore deep learning (DL) architectures, spectroscopic input types, and learning designs toward optimal quantification in MR spectroscopy of simulated pathological spectra; and (2) to demonstrate accuracy and… read more here.
Keywords: spectra deep; quantification spectra; learning; learning idealized ... See more keywords