18 citations · 36 across the 6 of their papers we have counts for
7 papers
A hybrid time-frequency parametric modelling of medical ultrasound signal transmission
Chiara Razzetta, Valentina Candiani, Marco Crocco +1
Medical ultrasound imaging is the most widespread real-time non-invasive imaging system and its formulation comprises signal transmission, signal reception, and image formation. Ul…
Physics-driven machine learning for the prediction of coronal mass ejections' travel times
Sabrina Guastavino, Valentina Candiani, Alessandro Bemporad +7
Coronal Mass Ejections (CMEs) correspond to dramatic expulsions of plasma and magnetic field from the solar corona into the heliosphere. CMEs are scientifically relevant because th…
A stochastic approach to delays optimization for narrowband transmit beam pattern in medical ultrasound
Chiara Razzetta, Valentina Candiani, Marco Crocco +1
Ultrasound imaging is extensively employed in clinical settings due to its non-ionizing nature and real-time capabilities. The beamformer represents a crucial component of an ultra…
Approximation error method for imaging the human head by electrical impedance tomography
Valentina Candiani, Nuutti Hyvönen, Jari P. Kaipio +1
This work considers electrical impedance tomography imaging of the human head, with the ultimate goal of locating and classifying a stroke in emergency care. One of the main diffic…
Neural networks for classification of strokes in electrical impedance tomography on a 3D head model
Valentina Candiani, Matteo Santacesaria
We consider the problem of the detection of brain hemorrhages from three dimensional (3D) electrical impedance tomography (EIT) measurements. This is a condition requiring urgent t…
Monotonicity-based reconstruction of extreme inclusions in electrical impedance tomography
Valentina Candiani, Jérémi Dardé, Henrik Garde +1
The monotonicity-based approach has become one of the fundamental methods for reconstructing inclusions in the inverse problem of electrical impedance tomography. Thus far the meth…
Computational framework for applying electrical impedance tomography to head imaging
Valentina Candiani, Antti Hannukainen, Nuutti Hyvönen
This work introduces a computational framework for applying absolute electrical impedance tomography to head imaging without accurate information on the head shape or the electrode…