Publications

2023

  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. N. Cibrario, M. Negro, N. Moriakov, R. Bonino, L. Baldini, N. Di Lalla, L. Latronico, S. Maldera, A. Manfreda, N. Omodei, C. Sgró, S. Tugliani, "Joint machine learning and analytic track reconstruction for X-ray polarimetry with gas pixel detectors", Astronomy & Astrophysics, 2023, 674

2022

  1. N. Moriakov, J. Sonke, J. Teuwen, "LIRE: Learned Invertible Reconstruction for Cone Beam CT", 2022
  2. Y. Beauferris, J. Teuwen, D. Karkalousos, N. Moriakov, M. Caan, G. Yiasemis, L. Rodrigues, A. Lopes, H. Pedrini, L. Rittner, M. Dannecker, V. Studenyak, F. Gröger, D. Vyas, S. Faghih-Roohi, A. Kumar Jethi, J. Chandra Raju, M. Sivaprakasam, M. Lasby, N. Nogovitsyn, W. Loos, R. Frayne, R. Souza, "Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations", Frontiers in Neuroscience, 2022, 16
  3. G. Yiasemis, N. Moriakov, D. Karkalousos, M. Caan, J. Teuwen, "DIRECT: Deep Image REConstruction Toolkit", Journal of Open Source Software, 2022, 7;(73):4278
  4. R. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen, R. M. Mann, "Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRI", Diagnostics, 2022, 12;(7):1690
  5. J. Peters, N. Moriakov, J. Van Dijck, S. Elias, E. Lips, J. Wesseling, R. Mann, J. Teuwen, M. Caballo, M. Broeders, "Prediction of histological grade and molecular subtypes of invasive breast cancer using mammographic growth rate in screening", European Journal of Cancer, 2022, 175

2021

  1. R. Sheombarsing, N. Moriakov, J. Sonke, J. Teuwen, "Subpixel object segmentation using wavelets and multi resolution analysis", 2021
  2. J. Teuwen, N. Moriakov, C. Fedon, M. Caballo, I. Reiser, P. Bakic, E. García, O. Diaz, K. Michielsen, I. Sechopoulos, "Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation", Medical Image Analysis, 2021, 71
  3. P. M. Johnson, G. Jeong, K. Hammernik, J. Schlemper, C. Qin, J. Duan, D. Rueckert, J. Lee, N. Pezzotti, E. De Weerdt, S. Yousefi, M. S. Elmahdy, J. H. F. Van Gemert, C. Schülke, M. Doneva, T. Nielsen, S. Kastryulin, B. P. F. Lelieveldt, M. J. P. Van Osch, M. Staring, E. Z. Chen, P. Wang, X. Chen, T. Chen, V. M. Patel, S. Sun, H. Shin, Y. Jun, T. Eo, S. Kim, T. Kim, D. Hwang, P. Putzky, D. Karkalousos, J. Teuwen, N. Moriakov, B. Bakker, M. Caan, M. Welling, M. J. Muckley, F. Knoll, "Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge", Machine Learning for Medical Image Reconstruction, 2021

2020

  1. Y. Beauferris, J. Teuwen, D. Karkalousos, N. Moriakov, M. Caan, G. Yiasemis, L. Rodrigues, A. Lopes, H. Pedrini, L. Rittner, M. Dannecker, V. Studenyak, F. Gröger, D. Vyas, S. Faghih-Roohi, A. K. Jethi, J. C. Raju, M. Sivaprakasam, M. Lasby, N. Nogovitsyn, W. Loos, R. Frayne, R. Souza, "Multi-Coil MRI Reconstruction Challenge – Assessing Brain MRI Reconstruction Models and their Generalizability to Varying Coil Configurations", 2020
  2. K. Michielsen, N. Moriakov, J. Teuwen, I. Sechopoulos, "Deep Learning-based Initialization of Iterative Reconstruction for Breast Tomosynthesis", 2020
  3. J. Teuwen, N. Moriakov, C. Fedon, M. Caballo, I. Reiser, P. Bakic, E. García, O. Diaz, K. Michielsen, I. Sechopoulos, "Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation", 2020
  4. N. Moriakov, J. Adler, J. Teuwen, "Kernel of CycleGAN as a Principle homogeneous space", 2020
  5. J. Teuwen, N. Moriakov, "Convolutional neural networks", Handbook of Medical Image Computing and Computer Assisted Intervention, 2020
  6. N. Moriakov, "Computable Følner monotilings and a theorem of Brudno", Ergodic Theory and Dynamical Systems, 2020, 41;(11):3389-3416

2019

  1. R. J. Dilz, L. Schröder, N. Moriakov, J. Sonke, J. Teuwen, "Learned SIRT for Cone Beam Computed Tomography Reconstruction", 2019
  2. J. Teuwen, N. Moriakov, R. Mann, E. Marchiori, J. Van Vugt, A. Gubern-Mérida, "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", Medical Imaging 2019: Computer-Aided Diagnosis, 2019
  3. P. Putzky, D. Karkalousos, J. Teuwen, N. Moriakov, B. Bakker, M. Caan, M. Welling, "i-RIM applied to the fastMRI challenge", 2019

2018

  1. J. v. Vugt, E. Marchiori, R. Mann, A. Gubern-Mérida, N. Moriakov, J. Teuwen, "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", 2018
  2. N. Moriakov, K. Michielsen, J. Adler, R. Mann, I. Sechopoulos, J. Teuwen, "Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction", 2018
  3. N. Moriakov, "Fluctuations of ergodic averages for actions of groups of polynomial growth", Studia Mathematica, 2018, 240;(3):255-273
  4. M. Haase, N. Moriakov, "On systems with quasi-discrete spectrum", Studia Mathematica, 2018, 241;(2):173-199

2017

  1. N. Moriakov, "On Effective Birkhoff’s Ergodic Theorem for Computable Actions of Amenable Groups", Theory of Computing Systems, 2017, 62;(5):1269-1287