| Using deep learning to accelerate magnetic resonance measurements of molecular exchange Z Cheng, S Hu, G Han, K Fang, X Jin, A Ordinola, E Özarslan, R Bai The Journal of Chemical Physics 159 (5), 2023 | 2 | 2023 |
| On the sampling strategies and models for measuring diffusion exchange with a double diffusion encoding sequence A Ordinola, S Cai, P Lundberg, R Bai, E Özarslan Magnetic Resonance Letters 3 (3), 232-247, 2023 | 2 | 2023 |
| Magnetic resonance measurement and reconstruction of the diffusion propagator AMO Santisteban, E Özarslan arXiv preprint arXiv:2106.16181, 2021 | 2 | 2021 |
| Magnetic resonance measurement and reconstruction of the diffusion propagator AM Ordinola Santisteban, E Özarslan arXiv e-prints, arXiv: 2106.16181, 2021 | 2 | 2021 |
| Limitations and generalizations of the first order kinetics reaction expression for modeling diffusion-driven exchange: Implications on NMR exchange measurements A Ordinola, E Özarslan, R Bai, M Herberthson The Journal of Chemical Physics 160 (8), 2024 | 1 | 2024 |
| Diffusion within pores fully revealed by magnetic resonance E Özarslan, C Yolcu, A Ordinola, D Boito, T Dela Haije, ... The Journal of Chemical Physics 158 (16), 2023 | | 2023 |
| Propagator-sensitive diffusion measurements hear the percussion ensemble E Özarslan, D Boito, A Ordinola | | |
| MR determination of the diffusion propagator: measurements on mouse spinal cord using a benchtop scanner A Ordinola, W Jackson, E Özarslan | | |
| MR measurement of the mean-position distribution A Ordinola, E Özarslan | | |
