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Results: 48
Number of items: 48
  • Open Access
    Williams, M. C., Weir-McCall, J. R., Baldassarre, L. A., De Cecco, C. N., Choi, A. D., Dey, D., Dweck, M. R., Isgum, I., Kolossvary, M., Leipsic, J., Lin, A., Lu, M. T., Motwani, M., Nieman, K., Shaw, L., van Assen, M., & Nicol, E. (2024). Artificial Intelligence and Machine Learning for Cardiovascular Computed Tomography (CCT): A White Paper of the Society of Cardiovascular Computed Tomography (SCCT). Journal of cardiovascular computed tomography, 18(6), 519–532. https://doi.org/10.1016/j.jcct.2024.08.003
  • Open Access
    Föllmer, B., Williams, M. C., Dey, D., Arbab-Zadeh, A., Maurovich-Horvat, P., Volleberg, R. H. J. A., Rueckert, D., Schnabel, J. A., Newby, D. E., Dweck, M. R., Guagliumi, G., Falk, V., Vázquez-Mézquita, A. J., Biavati, F., Išgum, I., & Dewey, M. (2024). Roadmap on the Use of Artificial Intelligence for Imaging of Vulnerable Atherosclerotic Plaque in Coronary Arteries. Nature Reviews. Cardiology, 21(1), 51-64. https://doi.org/10.1038/s41569-023-00900-3
  • Open Access
    Zoetmulder, R. (2023). Deep-learning-based image segmentation for uncommon ischemic stroke: From infants to adults. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Sander, J. (2023). Assessing anatomy and function of the heart using 4D cardiac MRI and deep learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Schreuder, A., Jacobs, C., Lessmann, N., Broeders, M. J. M., Silva, M., Išgum, I., de Jong, P. A., van den Heuvel, M. M., Sverzellati, N., Prokop, M., Pastorino, U., Schaefer-Prokop, C. M., & van Ginneken, B. (2022). Scan-based competing death risk model for re-evaluating lung cancer computed tomography screening eligibility. The European Respiratory Journal, 59(5), Article 2101613. https://doi.org/10.1183/13993003.01613-2021
  • van Velzen, S. G. M., Gal, R., Teske, A. J., van der Leij, F., van den Bongard, D. H. J. G., Viergever, M. A., Verkooijen, H. M., & Išgum, I. (2022). AI-Based Radiation Dose Quantification for Estimation of Heart Disease Risk in Breast Cancer Survivors After Radiation Therapy. International Journal of Radiation Oncology Biology Physics, 112(3), 621-632. https://doi.org/10.1016/j.ijrobp.2021.09.008
  • van Velzen, S. G. M., Bruns, S., Wolterink, J. M., Leiner, T., Viergever, M. A., Verkooijen, H. M., & Išgum, I. (2022). AI-Based Quantification of Planned Radiation Therapy Dose to Cardiac Structures and Coronary Arteries in Patients With Breast Cancer. International Journal of Radiation Oncology Biology Physics, 112(3), 611-620. https://doi.org/10.1016/j.ijrobp.2021.09.009
  • Open Access
    Bruns, S., Wolterink, J. M., van den Boogert, T. P. W., Runge, J. H., Bouma, B. J., Henriques, J. P., Baan, J., Viergever, M. A., Planken, R. N., & Išgum, I. (2022). Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT. Computers in Biology and Medicine, 142, Article 105191. https://doi.org/10.1016/j.compbiomed.2021.105191
  • Open Access
    Zoetmulder, R., Išgum, I., Gavves, E., & MR CLEAN Registry Investigators (2022). Deep-Learning-Based Thrombus Localization and Segmentation in Patients with Posterior Circulation Stroke. Diagnostics, 12(6), Article 1400. https://doi.org/10.3390/diagnostics12061400
  • Open Access
    Bruns, S. (2022). Automated segmentation of the heart in high-dimensional computed tomography. [Thesis, fully internal, Universiteit van Amsterdam].
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