20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction

no code implementations • 12 May 2021 • Omer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John Strupp, Cheryl A. Olman, Kâmil Uğurbil, Mehmet Akçakaya

High spatial and temporal resolution across the whole brain is essential to accurately resolve neural activities in fMRI.

Self-Supervised Learning

Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning

no code implementations • 10 May 2021 • Omer Burak Demirel, Burhaneddin Yaman, Logan Dowdle, Steen Moeller, Luca Vizioli, Essa Yacoub, John Strupp, Cheryl A. Olman, Kâmil Uğurbil, Mehmet Akçakaya

Self-supervised learning that does not require fully-sampled data has recently been proposed and has shown similar performance to supervised learning.

MRI Reconstruction Self-Supervised Learning

Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI

no code implementations • 13 Aug 2020 • Burhaneddin Yaman, Hongyi Gu, Seyed Amir Hossein Hosseini, Omer Burak Demirel, Steen Moeller, Jutta Ellermann, Kâmil Uğurbil, Mehmet Akçakaya

In this study, we propose an improved self-supervised learning strategy that more efficiently uses the acquired data to train a physics-guided reconstruction network without a database of fully-sampled data.

MRI Reconstruction Self-Supervised Learning