Dr. Sana Boudabbous | Clinical Neuroscience | Women Researcher Award
Dr. Sana Boudabbous | University Hopssalitals of Geneva | Switzerland
Neroladaki, A., Botsikas, D., Boudabbous, S., Becker, C. D., & Montet, X. (2013). Computed tomography of the chest with model-based iterative reconstruction using a radiation exposure similar to chest X-ray examination: Preliminary observations. European Radiology, 23(2), 360–366.
Mundada, P., Kohler, R., Boudabbous, S., Toutous Trellu, L., Platon, A., & Becker, C. D., et al. (2017). Injectable facial fillers: Imaging features, complications, and diagnostic pitfalls at MRI and PET CT. Insights into Imaging, 8(6), 557–572.
Boudabbous, S., Arditi, D., Paulin, E., Syrogiannopoulou, A., Becker, C., & Montet, X. (2015). Model-based iterative reconstruction (MBIR) for the reduction of metal artifacts on CT. American Journal of Roentgenology, 205(2), 380–385.
Botsikas, D., Triponez, F., Boudabbous, S., Hansen, C., Becker, C. D., & Montet, X. (2014). Incidental adrenal lesions detected on enhanced abdominal dual-energy CT: Can the diagnostic workup be shortened by the implementation of virtual unenhanced images? European Journal of Radiology, 83(10), 1746–1751.
Botsikas, D., Bagetakos, I., Picarra, M., Da Cunha Afonso Barisits, A. C., Boudabbous, S., & Montet, X., et al. (2019). What is the diagnostic performance of 18-FDG-PET/MR compared to PET/CT for the N- and M-staging of breast cancer? European Radiology, 29(4), 1787–1798.
Mundada, P., Becker, M., Lenoir, V., Stefanelli, S., Rougemont, A. L., Beaulieu, J. Y., … & Boudabbous, S. (2019). High resolution MRI of nail tumors and tumor-like conditions. European Journal of Radiology, 112, 93–105.
Delattre, B. M. A., Boudabbous, S., Hansen, C., Neroladaki, A., Hachulla, A. L., Becker, C. D., & Montet, X. (2020). Compressed sensing MRI of different organs: Ready for clinical daily practice? European Radiology, 30(1), 308–319.
Malinauskaite, I., Hofmeister, J., Burgermeister, S., Neroladaki, A., Hamard, M., Boudabbous, S., … & Montet, X. (2020). Radiomics and machine learning differentiate soft‐tissue lipoma and liposarcoma better than musculoskeletal radiologists. Sarcoma, 2020(1), Article 7163453.