Iterative training of robust k‐space interpolation networks for improved image reconstruction with limited scan specific training samples
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DOI: 10.1002/mrm.29482
Abstract: To evaluate an iterative learning approach for enhanced performance of robust artificial‐neural‐networks for k‐space interpolation (RAKI), when only a limited amount of training data (auto‐calibration signals [ACS]) are available for accelerated standard 2D imaging. read more here.
Keywords: training; space interpolation; iterative training; training robust ... See more keywords