Deep Algorithm Unrolling for Biomedical Imaging

Yuelong Li, Or Bar-Shira, Vishal Monga, Yonina C Eldar

Research output: Contribution to journalArticle

Abstract

In this chapter, we review biomedical applications and breakthroughs via leveraging algorithm unrolling, an important technique that bridges between traditional iterative algorithms and modern deep learning techniques. To provide context, we start by tracing the origin of algorithm unrolling and providing a comprehensive tutorial on how to unroll iterative algorithms into
deep networks. We then extensively cover algorithm unrolling in a wide variety of biomedical imaging modalities and delve into several representative recent works in detail. Indeed, there is a rich history of iterative algorithms for biomedical image synthesis, which makes the field ripe for unrolling techniques. In addition, we put algorithm unrolling into a broad perspective,
in order to understand why it is particularly effective and discuss recent trends. Finally, we conclude the chapter by discussing open challenges, and suggesting future research directions.
Original languageEnglish
Number of pages34
JournalArXiv.org.
StatePublished - 14 Aug 2021

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