Research output per year
Research output per year
Personal profile
specialisation
Artificial Intelligence in Medical Imaging
Research interests
My research focuses on accelerated-MRI reconstruction using deep learning. I am currently working in Stroke treatment decision support by Artificial Intelligence for analysis of MR images (STAIRS),aiming to accelerate MR Imaging and detection of stroke in the acute setting.
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
MultiTask Learning for accelerated-MRI Reconstruction and Segmentation of Brain Lesions in Multiple Sclerosis
Karkalousos, D., Išgum, I., Marquering, H. A. & Caan, M. W. A., 2023, Medical Imaging with Deep Learning 2023, MIDL 2023. Oguz, I., Noble, J., Li, X., Styner, M., Baumgartner, C., Rusu, M., Heinmann, T., Kontos, D., Landman, B. & Dawant, B. (eds.). ML Research Press, Vol. 227. p. 991-1005 (Proceedings of Machine Learning Research).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
1 Citation (Scopus) -
Assessment of data consistency through cascades of independently recurrent inference machines for fast and robust accelerated MRI reconstruction
Karkalousos, D., Noteboom, S., Hulst, H. E., Vos, F. M. & Caan, M. W. A., 21 Jun 2022, In: Physics in medicine and biology. 67, 12, 124001.Research output: Contribution to journal › Article › Academic › peer-review
Open Access7 Citations (Scopus) -
A unified model for reconstruction and R2* mapping of accelerated 7T data using the quantitative recurrent inference machine
Zhang, C., Karkalousos, D., Bazin, P-L., Coolen, B. F., Vrenken, H., Sonke, J-J., Forstmann, B. U., Poot, D. H. J. & Caan, M. W. A., 1 Dec 2022, In: NEUROIMAGE. 264, 13 p., 119680.Research output: Contribution to journal › Article › Academic › peer-review
Open Access6 Citations (Scopus) -
Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations
Beauferris, Y., Teuwen, J., Karkalousos, D., Moriakov, N., Caan, M., Yiasemis, G., Rodrigues, L. V., Lopes, A., Pedrini, H., Rittner, L., Dannecker, M., Studenyak, V., Gröger, F., Vyas, D., Faghih-Roohi, S., Kumar Jethi, A., Chandra Raju, J., Sivaprakasam, M., Lasby, M., Nogovitsyn, N., & 3 others, 6 Jul 2022, In: Frontiers in neuroscience. 16, 919186.Research output: Contribution to journal › Article › Academic › peer-review
Open Access12 Citations (Scopus) -
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge
Johnson, P. M., Jeong, G., Hammernik, K., Schlemper, J., Qin, C., Duan, J., Rueckert, D., Lee, J., Pezzotti, N., de Weerdt, E., Yousefi, S., Elmahdy, M. S., van Gemert, J. H. F., Schülke, C., Doneva, M., Nielsen, T., Kastryulin, S., Lelieveldt, B. P. F., van Osch, M. J. P., Staring, M., & 21 others, 2021, Machine Learning for Medical Image Reconstruction - 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Proceedings. Haq, N., Johnson, P., Maier, A., Würfl, T. & Yoo, J. (eds.). Springer Science and Business Media Deutschland GmbH, Vol. 12964 LNCS. p. 25-34 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12964 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
2 Citations (Scopus)