Towards in vivo ground truth susceptibility for single-orientation deep learning QSM: A multi-orientation gradient-echo MRI dataset

• Published in: NeuroImage (Orlando, Fla.) Vol. 261; p. 119522
• Main Authors: Shi, Yuting, Feng, Ruimin, Li, Zhenghao, Zhuang, Jie, Zhang, Yuyao, Wei, Hongjiang
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.11.2022; Elsevier Limited; Elsevier
• Subjects: Algorithms; Alzheimer's disease; Benchmark; Brain; Data processing; Datasets; Deep learning; Hemorrhage; Magnetic resonance imaging; Multi-orientation GRE dataset; Multiple sclerosis; Neural networks; Quantitative susceptibility mapping; Substantia grisea; Susceptibility; Deep learning; Benchmark; Quantitative susceptibility mapping; Multi-orientation GRE dataset

Recently, deep neural networks have shown great potential for solving dipole inversion of quantitative susceptibility mapping (QSM) with improved results. However, these studies utilized their limited dataset for network training and inference, which may lead to untrustworthy conclusions. Thus, a co...