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  1. 2020
  2. Rodionov, R., O'Keeffe, A., Nowell, M., Rizzi, M., Vakharia, V. N., Wykes, V., ... Duncan, J. S. (2020). Increasing the accuracy of 3D EEG implantations. Journal of Neurosurgery, 133(1), 35-42. https://doi.org/10.3171/2019.2.JNS183313
  3. Prados, F., Moccia, M., Johnson, A., Yiannakas, M., Grussu, F., Cardoso, M. J., ... Wheeler-Kingshott, C. (2020). Generalised boundary shift integral for longitudinal assessment of spinal cord atrophy. NeuroImage, 209, [116489]. https://doi.org/10.1016/j.neuroimage.2019.116489
  4. Ranzini, M. B. M., Groothuis, I., Klaser, K., Cardoso, M. J., Henckel, J., Ourselin, S., ... Modat, M. (2020). Combining Multimodal Information for Metal Artefact Reduction: An Unsupervised Deep Learning Framework. In ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging (pp. 600-604). [9098633] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2020-April). IEEE Computer Society. https://doi.org/10.1109/ISBI45749.2020.9098633
  5. Granados, A., Lucena, O., Vakharia, V., Miserocchi, A., McEvoy, A. W., Vos, S. B., ... Ourselin, S. (2020). Towards Uncertainty Quantification for Electrode Bending Prediction in Stereotactic Neurosurgery. In ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging (pp. 674-677). [9098730] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2020-April). IEEE Computer Society. https://doi.org/10.1109/ISBI45749.2020.9098730
  6. Krimphove, M. J., Reese, S., Chen, X., Marchese, M., Cone, E., Tully, K. H., ... Trinh, Q-D. (2020). Minimally invasive cancer surgery is associated with a lower risk of venous thromboembolic events. Journal of Surgical Oncology, 121(3), 578-583. https://doi.org/10.1002/jso.25832
  7. Uro-technology and SoMe Working Group of the Young Academic Urologists Working Party of the European Association of Urology (2020). Artificial intelligence and neural networks in urology: current clinical applications. Minerva urologica e nefrologica = The Italian journal of urology and nephrology, 72(1), 49-57. https://doi.org/10.23736/S0393-2249.19.03613-0
  8. Lillington, J., Brusaferri, L., Kläser, K., Shmueli, K., Neji, R., Hutton, B. F., ... Atkinson, D. (2020). PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques. Medical physics, 47(2), 790-811. https://doi.org/10.1002/mp.13943
  9. Chung, K. K., Altmann, D., Barkhof, F., Miszkiel, K., Brex, P. A., O'Riordan, J., ... Chard, D. T. (2020). A 30-Year Clinical and Magnetic Resonance Imaging Observational Study of Multiple Sclerosis and Clinically Isolated Syndromes. Annals of Neurology, 87(1), 63-74. https://doi.org/10.1002/ana.25637
  10. Chen, M. Y., Skewes, J., Desselle, M., Wong, C., Woodruff, M. A., Dasgupta, P., & Rukin, N. J. (2020). Current applications of three-dimensional printing in urology. BJU International, 125(1), 17-27. https://doi.org/10.1111/bju.14928
  11. Mehta, P., Antonelli, M., Ahmed, H., Emberton, M., Punwani, S., & Ourselin, S. (2020). Decision fusion of 3D convolutional neural networks to triage patients with suspected prostate cancer using volumetric biparametric MRI. In H. K. Hahn, & M. A. Mazurowski (Eds.), Medical Imaging 2020: Computer-Aided Diagnosis [1131433] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11314). SPIE. https://doi.org/10.1117/12.2547682
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