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Results: 48
Number of items: 48
  • Open Access
    Dobrolinska, M. M., Jukema, R. A., van Velzen, S. G. M., van Diemen, P. A., Greuter, M. J. W., Prakken, N. H. J., van der Werf, N. R., Raijmakers, P. G., Slart, R. H. J. A., Knaapen, P., Isgum, I., & Danad, I. (2024). The prognostic value of visual and automatic coronary calcium scoring from low-dose computed tomography-[15O]-water positron emission tomography. European Heart Journal Cardiovascular Imaging, 25(9), 1186-1196. https://doi.org/10.1093/ehjci/jeae081
  • Open Access
    Oudkerk Pool, M. D. (2024). Innovations in cardiology: Towards patient centered care. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kolk, M. Z. H., Ruipérez-Campillo, S., Allaart, C. P., Wilde, A. A. M., Knops, R. E., Narayan, S. M., Tjong, F. V. Y., & DEEP RISK investigators (2024). Multimodal explainable artificial intelligence identifies patients with non-ischaemic cardiomyopathy at risk of lethal ventricular arrhythmias. Scientific Reports, 14, Article 14889. https://doi.org/10.1038/s41598-024-65357-x
  • 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. In I. Sack, & T. Schaeffter (Eds.), Quantification of Biophysical Parameters in Medical Imaging (2nd ed., pp. 547–568). Springer. https://doi.org/10.1007/978-3-031-61846-8_27
  • Open Access
    Hampe, N., van Velzen, S. G. M., Wolterink, J. M., Collet, C., Henriques, J. P. S., Planken, N., & Išgum, I. (2024). Graph neural networks for automatic extraction and labeling of the coronary artery tree in CT angiography. Journal of Medical Imaging, 11(03), Article 034001 . https://doi.org/10.1117/1.jmi.11.3.034001
  • Open Access
    van de Vijver, W. R., Hennecken, J., Lagogiannis, I., Pérez del Villar, C., Herrera, C., Douek, P. C., Segev, A., Hovingh, G. K., Išgum, I., Winter, M. M., Planken, R. N., & Claessen, B. E. P. M. (2024). The Role of Coronary Computed Tomography Angiography in the Diagnosis, Risk Stratification, and Management of Patients with Diabetes and Chest Pain. Reviews in Cardiovascular Medicine, 25(12), Article 442. https://doi.org/10.31083/j.rcm2512442
  • Open Access
    Galanty, M., Luitse, D., Noteboom, S. H., Croon, P., Vlaar, A. P., Poell, T., Sánchez Gutiérrez, C. I., Blanke, T., & Išgum, I. (2024). Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool. Scientific Reports, 14, Article 31846. https://doi.org/10.1038/s41598-024-83218-5
  • Open Access
    Karkalousos, D., Išgum, I., Marquering, H. A., & Caan, M. W. A. (2024). Atommic: An Advanced Toolbox for Multitask Medical Imaging Consistency to Facilitate Artificial Intelligence Applications from Acquisition to Analysis in Magnetic Resonance Imaging. Computer Methods and Programs in Biomedicine, 256, Article 108377. https://doi.org/10.1016/j.cmpb.2024.108377
  • Open Access
    Płotka, S. S. (2024). Enhancing prenatal care through deep learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    van Harten, L. D. (2024). Motion analysis in 4D MRI of the small intestine using neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
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