Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 48
Number of items: 48
  • Sander, J., de Vos, B. D., & Išgum, I. (2021). Unsupervised super-resolution: Creating high-resolution medical images from low-resolution anisotropic examples. In I. Išgum, & B. A. Landman (Eds.), Medical Imaging 2021: Image Processing: 15-19 February 2021, online only, Unitred States (Vol. 1). Article 115960E (Proceedings of SPIE; Vol. 11596), (Progress in Biomedical Optics and Imaging; Vol. 22, No. 2). SPIE. https://doi.org/10.1117/12.2580412
  • Open Access
    Schuuring, M. J., Išgum, I., Cosyns, B., Chamuleau, S. A. J., & Bouma, B. J. (2021). Routine Echocardiography and Artificial Intelligence Solutions. Frontiers in Cardiovascular Medicine, 8, Article 648877. https://doi.org/10.3389/fcvm.2021.648877
  • Open Access
    Dekker, M., Waissi, F., Silvis, M. J. M., Bennekom, J. V., Schoneveld, A. H., de Winter, R. J., Isgum, I., Lessmann, N., Velthuis, B. K., Pasterkamp, G., Mosterd, A., Timmers, L., & de Kleijn, D. P. V. (2021). High levels of osteoprotegerin are associated with coronary artery calcification in patients suspected of a chronic coronary syndrome. Scientific Reports, 11, Article 18946. https://doi.org/10.1038/s41598-021-98177-4
  • Open Access
    Gal, R., Gregorowitsch, M. L., Emaus, M. J., Blezer, E. L. A., van der Leij, F., van Velzen, S. G. M., van Tol-Geerdink, J. J., Išgum, I., & Verkooijen, H. M. (2021). Coronary artery calcifications on breast cancer radiotherapy planning CT scans and cardiovascular risk: What do patients want to know? International journal of cardiology. Cardiovascular risk and prevention, 11, Article 200113. https://doi.org/10.1016/j.ijcrp.2021.200113
  • Open Access
    Zoetmulder, R., Konduri, P. R., Obdeijn, I. V., Gavves, E., Išgum, I., Majoie, C. B. L. M., Dippel, D. W. J., Roos, Y. B. W. E. M., Goyal, M., Mitchell, P. J., Campbell, B. C. V., Lopes, D. K., Reimann, G., Jovin, T. G., Saver, J. L., Muir, K. W., White, P., Bracard, S., Chen, B., ... Marquering, H. A. (2021). Automated final lesion segmentation in posterior circulation acute ischemic stroke using deep learning. Diagnostics, 11(9), Article 1621. https://doi.org/10.3390/diagnostics11091621
  • Open Access
    Slart, R. H. J. A., Williams, M. C., Juarez-Orozco, L. E., Rischpler, C., Dweck, M. R., Glaudemans, A. W. J. M., Gimelli, A., Georgoulias, P., Gheysens, O., Gaemperli, O., Habib, G., Hustinx, R., Cosyns, B., Verberne, H. J., Hyafil, F., Erba, P. A., Lubberink, M., Slomka, P., Išgum, I., ... Saraste, A. (2021). Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT. European Journal of Nuclear Medicine and Molecular Imaging, 48(5), 1399-1413. https://doi.org/10.1007/s00259-021-05341-z
  • Open Access
    Dekker, M., Waissi, F., Bank, I. E. M., Isgum, I., Scholtens, A. M., Velthuis, B. K., Pasterkamp, G., de Winter, R. J., Mosterd, A., Timmers, L., & de Kleijn, D. P. V. (2021). The prognostic value of automated coronary calcium derived by a deep learning approach on non-ECG gated CT images from 82Rb-PET/CT myocardial perfusion imaging. International Journal of Cardiology, 329, 9-15. https://doi.org/10.1016/j.ijcard.2020.12.079
  • Open Access
    Khalili, N., Turk, E., Benders, M. J. N. L., Moeskops, P., Claessens, N. H. P., de Heus, R., Franx, A., Wagenaar, N., Breur, J. M. P. J., Viergever, M. A., & Išgum, I. (2019). Automatic extraction of the intracranial volume in fetal and neonatal MR scans using convolutional neural networks. NeuroImage: Clinical, 24, Article 102061. https://doi.org/10.1016/j.nicl.2019.102061
Page 5 of 5