Skip to main navigation Skip to search Skip to main content

Artificial Intelligence and Stroke Imaging: A West Coast Perspective

  • Guangming Zhu
  • , Bin Jiang
  • , Hui Chen
  • , Elizabeth Tong
  • , Yuan Xie
  • , Tobias D. Faizy
  • , Jeremy J. Heit
  • , Greg Zaharchuk
  • , Max Wintermark

Research output: Contribution to journalReview articlepeer-review

Abstract

Artificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intense research. AI techniques are well-suited for dealing with vast amounts of stroke imaging data and a large number of multidisciplinary approaches used in classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. This article addresses this topic and seeks to present an overview of machine learning and/or deep learning applied to stroke imaging.

Original languageEnglish (US)
Pages (from-to)479-492
Number of pages14
JournalNeuroimaging Clinics of North America
Volume30
Issue number4
DOIs
StatePublished - Nov 2020
Externally publishedYes

Keywords

  • Artificial intelligence
  • Deep learning
  • Machine learning
  • Stroke imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

Fingerprint

Dive into the research topics of 'Artificial Intelligence and Stroke Imaging: A West Coast Perspective'. Together they form a unique fingerprint.

Cite this