1 code implementation • 2 Dec 2021 • Mehmet Yigit Avci, Ziyu Li, Qiuyun Fan, Susie Huang, Berkin Bilgic, Qiyuan Tian
Dropout is conventionally used during the training phase as regularization method and for quantifying uncertainty in deep learning.
1 code implementation • 14 Nov 2021 • Qiyuan Tian, Ziyu Li, Qiuyun Fan, Jonathan R. Polimeni, Berkin Bilgic, David H. Salat, Susie Y. Huang
The noise in diffusion-weighted images (DWIs) decreases the accuracy and precision of diffusion tensor magnetic resonance imaging (DTI) derived microstructural parameters and leads to prolonged acquisition time for achieving improved signal-to-noise ratio (SNR).
1 code implementation • 17 Feb 2021 • Qiyuan Tian, Ziyu Li, Qiuyun Fan, Chanon Ngamsombat, Yuxin Hu, Congyu Liao, Fuyixue Wang, Kawin Setsompop, Jonathan R. Polimeni, Berkin Bilgic, Susie Y. Huang
High-resolution diffusion tensor imaging (DTI) is beneficial for probing tissue microstructure in fine neuroanatomical structures, but long scan times and limited signal-to-noise ratio pose significant barriers to acquiring DTI at sub-millimeter resolution.