Published February 2021 | Version v1
Journal article

Artificial intelligence and deep learning in neuroradiology: exploring the new frontier

  • 1. McMaster University, Department of Radiology, Hamilton, Ontario (Canada)
  • 2. McMaster University, Hamilton General Hospital, Department of Radiology, Hamilton, Ontario (Canada)

Description

There have been many recently published studies exploring machine learning (ML) and deep learning applications within neuroradiology. The improvement in performance of these techniques has resulted in an ever-increasing number of commercially available tools for the neuroradiologist. In this narrative review, recent publications exploring ML in neuroradiology are assessed with a focus on several key clinical domains. In particular, major advances are reviewed in the context of: (1) intracranial hemorrhage detection, (2) stroke imaging, (3) intracranial aneurysm screening, (4) multiple sclerosis imaging, (5) neuro-oncology, (6) head and tumor imaging, and (7) spine imaging. (author)

Availability note (English)

Available from DOI: https://doi.org/10.1177/0846537120954293

Additional details

Identifiers

Publishing Information

Journal Title
Canadian Association of Radiologists Journal
Journal Volume
72
Journal Issue
1
Journal Page Range
p. 35-44
ISSN
0846-5371

INIS

Country of Publication
Canada
Country of Input or Organization
Canada
INIS RN
53059747
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
ARTIFICIAL INTELLIGENCE; DIAGNOSTIC TECHNIQUES; IONOGRAPHIC IMAGING; NUCLEAR MEDICINE; RADIOLOGY
Descriptors DEC
BIOMEDICAL RADIOGRAPHY; DIAGNOSTIC TECHNIQUES; MEDICINE; NUCLEAR MEDICINE; RADIOLOGY

Optional Information

Notes
65 refs., 2 tabs., 4 figs.