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
Multi-Weight Respecification of Scan-specific Learning for Parallel Imaging
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic resonance imaging"
DOI: 10.48550/arxiv.2204.01979
Abstract: Parallel imaging is widely used in magnetic resonance imaging as an acceleration technology. Traditional linear reconstruction methods in parallel imaging often suffer from noise amplification. Recently, a non-linear robust artificial-neural-network for k-space interpolation (RAKI) exhibits… read more here.
Keywords: parallel imaging; multi weight; respecification scan; raki ... See more keywords