339 citations · 422 across the 3 of their papers we have counts for
3 papers
Fast MRI for All: Bridging Access Gaps by Training without Raw Data
Yaşar Utku Alçalar, Merve Gülle, Mehmet Akçakaya
Physics-driven deep learning (PD-DL) approaches have become popular for improved reconstruction of fast magnetic resonance imaging (MRI) scans. Though PD-DL offers higher accelerat…
Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement
Mehmet Akçakaya, Burhaneddin Yaman, Hyungjin Chung +1
Recently, deep learning approaches have become the main research frontier for biological image reconstruction and enhancement problems thanks to their high performance, along with…
Self-Supervised Learning of Physics-Guided Reconstruction Neural Networks without Fully-Sampled Reference Data
Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller +3
Purpose: To develop a strategy for training a physics-guided MRI reconstruction neural network without a database of fully-sampled datasets. Theory and Methods: Self-supervised lea…