1.Y. Qiao, and Y. Shi, “Unsupervised Deep Learning for FOD-Based Susceptibility Distortion Correction in Diffusion MRI," IEEE Transactions on Medical Imaging, 10.1109/TMI.2021.3134496, Dec. 2021. (中科院一区，影响因子10.048)

2.Y. Qiao, W. Sun and Y. Shi, “FOD-based Registration for Susceptibility Distortion Correction in ConnectomeImaging," NeuroImage, 202, p.116164. 2019. (中科院一区，影响因子6.556)

3.W. Sun, Y. Tang,Y. Qiao, et al.. “A probabilistic atlas of locus coeruleus pathways to transentorhinal cortex for connectome imaging in Alzheimer's disease," NeuroImage, 117301. 2020.(共同一作，中科院一区，影响因子6.556)

4.Y. Qiao, B.P.F. Lelieveldt and M. Staring, “An Efficient Preconditioner for Stochastic Gradient Descent Optimization of Image Registration," IEEE Transactions on Medical Imaging, vol. 38, no. 10, pp. 2314-2325,Oct. 2019. (中科院一区，影响因子10.048)

5.Y. Qiao, T. Jagt, M. Hoogeman, B.P.F. Lelieveldt and M. Staring, “Evaluation of an open source registration package for automatic contour propagation in online adaptive intensity-modulated proton therapy of prostatecancer," Frontiers in Oncology, 9 (2019): 1297. (中科院二区，影响因子6.244)

6.Y. Qiao, B. van Lew, B.P.F. Lelieveldt and M. Staring, “Fast Automatic Step Size Estimation for Gradient Descent Optimization of Image Registration," IEEE Transactions on Medical Imaging, vol. 35 (2), pp. 391-403,2016. (中科院一区，影响因子10.048)