Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI

1 code implementation • 1 Feb 2019 • Thomas Sanchez, Baran Gözcü, Ruud B. van Heeswijk, Armin Eftekhari, Efe Ilıcak, Tolga Çukur, Volkan Cevher

Compressed sensing applied to magnetic resonance imaging (MRI) allows to reduce the scanning time by enabling images to be reconstructed from highly undersampled data.

Learning-Based Compressive MRI

no code implementations • 3 May 2018 • Baran Gözcü, Rabeeh Karimi Mahabadi, Yen-Huan Li, Efe Ilıcak, Tolga Çukur, Jonathan Scarlett, Volkan Cevher

In the area of magnetic resonance imaging (MRI), an extensive range of non-linear reconstruction algorithms have been proposed that can be used with general Fourier subsampling patterns.

Anatomy Learning Theory