Neural current imaging aims at analyzing the functionality of the human brain through the localization of those regions where the neural current flows. The reconstruction of an electric current distribution from its magnetic field measured in the outer space, gives rise to a highly ill-posed and ill-conditioned inverse problem. We use a joint sparsity constraint as a regularization term and we propose an efficient iterative thresholding algorithm to recover the current distribution. Some numerical tests are also displayed.
AN ITERATIVE THRESHOLDING ALGORITHM FOR THE NEURAL CURRENT IMAGING / Bretti, Gabriella; Pitolli, Francesca. - STAMPA. - 82:(2010), pp. 134-145. (Intervento presentato al convegno 9th Conference of the Italian-Society-for-Applied-and-Industrial-Mathematics tenutosi a Rome, ITALY nel SEP 15-19, 2008) [10.1142/9789814280303_0012].
AN ITERATIVE THRESHOLDING ALGORITHM FOR THE NEURAL CURRENT IMAGING
BRETTI, GABRIELLA;PITOLLI, Francesca
2010
Abstract
Neural current imaging aims at analyzing the functionality of the human brain through the localization of those regions where the neural current flows. The reconstruction of an electric current distribution from its magnetic field measured in the outer space, gives rise to a highly ill-posed and ill-conditioned inverse problem. We use a joint sparsity constraint as a regularization term and we propose an efficient iterative thresholding algorithm to recover the current distribution. Some numerical tests are also displayed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
