{'fraction_non_alphanumeric': 0.01932367149758454, 'fraction_numerical': 0.0, 'mean_word_length': 5.282828282828283, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Calibration-Free Accelerated Dynamic MRI based on Low-Rank Matrix Recovery

Parallel magnetic resonance (MR) imaging techniques use multiple receiver coils for data acquisition. Sensitivity responses of these coils usually vary in space and must be estimated via a separate calibration process. We present an algorithm for jointly estimating MR images and coil sensitivity maps from subsampled k-space measurements. We pose the joint estimation problem as the recovery of a rank-one matrix from coded, linear measurements. We demonstrate the performance of our method on cardiac MRI datasets with multiple receiver coils.