About

Nikita Moriakov is a postdoctoral researcher working on developing novel AI methodologies for Oncology. Previously he obtained his Master's degree in Applied Mathematics from Delft University of Technology in 2012 (cum laude). In October 2016 he received his Ph.D. at the same university, defending thesis Entropy and Kolmogorov Complexity. He is currently working on the cancer risk prediction in breast imaging, and the reconstruction of cone-beam CT (CBCT) images in adaptive radiotherapy. His supervisors are Jonas Teuwen and Jan-Jakob Sonke.

Last 5 publications

1. N. Moriakov, J. Peters, R. Mann, N. Karssemeijer, J. V. Dijck, M. Broeders, J. Teuwen, "Improving Lesion Volume Measurements on Digital Mammograms", 2023
2. S. A. M. Tunissen, L. J. Oostveen, N. Moriakov, J. Teuwen, K. Michielsen, E. J. Smit, I. Sechopoulos, "Development, validation, and simplification of a scanner‐specific CT simulator", Medical Physics, 2023
3. G. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, "vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-Problems", 2023
4. G. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, "Deep Cardiac MRI Reconstruction with ADMM", 2023
5. N. Moriakov, J. Sonke, J. Teuwen, "End‐to‐end memory‐efficient reconstruction for cone beam CT", Medical Physics, 2023