Manuel Taso1, Uri Wollner2, Arnaud Guidon3, Rafi Barda2, Christopher J Hardy4, Sangtae Ahn4, and David C Alsop1
1Division of MRI research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, 2GE Research, Herzliya, Israel, 3Global MR Applications and Workflow, GE Healthcare, Boston, MA, United States, 4GE Research, Niskayuna, NY, United States
1Division of MRI research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, 2GE Research, Herzliya, Israel, 3Global MR Applications and Workflow, GE Healthcare, Boston, MA, United States, 4GE Research, Niskayuna, NY, United States
Arterial spin labeling (ASL) has proven to be a powerful research and clinical technique for functional imaging of tissues. This work explores the feasibility and performance of Deep-Learning based reconstruction for fast volumetric perfusion imaging with ASL.
Figure 2 – comparison between L1-wavelet CS and DCI-net reconstructions at various rates
Figure 1 – Illustration of the architecture of DCI-Net with 2D convolution.