Publications
Grisanti, S., Garbarino, S., Bellucci, M., Schenone, C., Candiani, V., Di Lillo, S., Campi, C., Barisione, E., Aloè, T., Tagliabue, E., Serventi, A., Pesce, G., Massucco, S., Cabona, C., Lechiara, A., Uccelli, A., Schenone, A., Piana, M., Benedetti, L., Neurological long-COVID in the outpatient clinic: is it so long?, accepted in European Journal of Neurology, September 2024.
Razzetta, C., Candiani, V., Crocco, M., Benvenuto, F., A stochastic approach to delays optimization for narrowband transmit beam pattern in medical ultrasound, Discover Applied Sciences, 2024, 6, 370.
Toivanen, J., Paldanius, A., Dekdouk, B., Candiani, V., Hänninen, A., Savolainen, T., Strbian, D., Forss, N., Hyvönen, N., Hyttinen, J., Kolehmainen, V., A Simulation-based Feasibility Study of Monitoring of Intracerebral Hemorrhages and Detection of Secondary Hemorrhages Using Electrical Impedance Tomography, Journal of Medical Imaging, 11(1), 014502, 2024.
Razzetta, C., Candiani, V., Crocco, M., Benvenuto, F., Hybrid time-frequency parametric modelling of medical ultrasound signal transmission, Advances of Computational Science and Engineering, 2023, 1(3): 249-270.
Guastavino, S., Candiani, V., Bemporad, A., Marchetti, F., Benvenuto, F., Massone, A. M., Susino, R., Telloni, D., Fineschi, S., Piana, M., Physics-driven machine learning for the prediction of coronal mass ejections' travel times, The Astrophysical Journal, 2023, 954(2): 151.
Telloni, D., Lo Schiavo, M., Magli, E., Fineschi, S., Guastavino, S., Nicolini, G., Susino, R., Giordano, S., Amadori, F., Candiani, V., Piana, M., and Massone, A. M., Prediction Capability of Geomagnetic Events from Solar Wind Data using Machine Learning Techniques, The Astrophysical Journal, 2023, 952(2): 111.
Cama, I., Candiani, V., Roccatagliata, L., Fiaschi, P., Rebella, G., Resaz, M., Piana, M., and Campi, C., Segmentation agreement and the reliability of radiomics features, Advances of Computational Science and Engineering, 2023, 1(2): 202-217.
Candiani, V., Computational approaches in electrical impedance tomography with applications to head imaging, Aalto University publication series Doctoral Dissertation 139/2021, November 2021.
Candiani, V., Hyvönen, N., Kaipio, J. P., Kolehmainen, V., Approximation error method for imaging the human head by electrical impedance tomography, Inverse Problems, 37(12), 125008, 2021.
Candiani, V., Santacesaria, M., Neural networks for classification of stroke in electrical impedance tomography on a 3D head model, Mathematics in Engineering, 4(4), 1-22, 2021.
Candiani, V., Dardé, J., Garde, H., Hyvönen, N., Monotonicity-based reconstruction of extreme inclusions in electrical impedance tomography, SIAM J. Math. Analysis, 52(6), 6234-6259, 2020.
Candiani, V., Hannukainen, A., Hyvönen, N., Computational framework for applying electrical impedance tomography to head imaging, SIAM J. Sci. Comput., 41(5), B1034-B1060, 2019.