no code implementations • 30 Apr 2024 • Abdoljalil Addeh, Fernando Vega, Rebecca J. Williams, G. Bruce Pike, M. Ethan MacDonald
Motivation: In many fMRI studies, respiratory signals are often missing or of poor quality.
1 code implementation • 14 Nov 2023 • Yang Gao, Zhuang Xiong, Shanshan Shan, Yin Liu, Pengfei Rong, Min Li, Alan H Wilman, G. Bruce Pike, Feng Liu, Hongfu Sun
The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a self-supervised manner on a specially-designed simulation brain dataset.
no code implementations • 3 Jul 2023 • Abdoljalil Addeh, Fernando Vega, Rebecca J Williams, Ali Golestani, G. Bruce Pike, M. Ethan MacDonald
In many fMRI studies, respiratory signals are unavailable or do not have acceptable quality.
2 code implementations • 15 Nov 2021 • Yang Gao, Zhuang Xiong, Amir Fazlollahi, Peter J Nestor, Viktor Vegh, Fatima Nasrallah, Craig Winter, G. Bruce Pike, Stuart Crozier, Feng Liu, Hongfu Sun
In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the novel neural networks.
1 code implementation • 17 Mar 2021 • Yang Gao, Martijn Cloos, Feng Liu, Stuart Crozier, G. Bruce Pike, Hongfu Sun
In this study, a learning-based Deep Complex Residual Network (DCRNet) is proposed to recover both the magnitude and phase images from incoherently undersampled data, enabling high acceleration of QSM acquisition.