Iterative training of robust k‐space interpolation networks for improved image reconstruction with limited scan specific training samples
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
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
Optimized fast GPU implementation of robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction
Sign Up to like & getrecommendations! Published in 2019 at "PLoS ONE"
DOI: 10.1371/journal.pone.0223315
Abstract: Background Robust Artificial-neural-networks for k-space Interpolation (RAKI) is a recently proposed deep-learning-based reconstruction algorithm for parallel imaging. Its main premise is to perform k-space interpolation using convolutional neural networks (CNNs) trained on subject-specific autocalibration signal… read more here.
Keywords: cnn architecture; neural networks; space interpolation; raki ... See more keywords