Learnable Douglas-Rachford iteration and its applications in DOT imaging

Volume: 14, Issue: 4, Pages: 683 - 700
Published: Jan 1, 2020
Abstract

How to overcome the ill-posed nature of inverse problems is a pervasive problem in medical imaging. Most existing solutions are based on regularization techniques. This paper proposed a deep neural network (DNN) based image reconstruction method, the so-called DR-Net, that leverages the interpretability of existing regularization methods and adaptive modeling capacity of DNN. Motivated by a Douglas-Rachford...

Paper Details
Title
Learnable Douglas-Rachford iteration and its applications in DOT imaging
Published Date
Jan 1, 2020
Volume
14
Issue
4
Pages
683 - 700
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.