Undersampled Multi Coil Image Reconstruction for Fast FMRI Using Adaptive Linear Neurons

Thimo Grotz¹, Benjamin Zahneisen¹, Marco Reisert¹, Maxim Zaitsev¹, Jrgen Hennig¹

Standard fMRI experiments have a rather limited temporal resolution of 1-3s. The temporal resolution of fMRI experiments can be increased by an order of magnitude by acquiring less k-space and using a high number of receive channels. Image reconstruction is thus an ill-posed inverse problem. Here we would like to introduce a new approach, based on neural networks, to reconstruct the undersampled fMRI data that offers a significantly improved point spread function with reduced spatial spread and hence improved spatial localization of activation.