Artificial Intelligence Applications in Intracranial Aneurysm: Achievements, Challenges and Opportunities.

Artificial Intelligence Computer-assisted Diagnosis Imaging Intracranial Aneurysm Machine Learning

Journal

Academic radiology
ISSN: 1878-4046
Titre abrégé: Acad Radiol
Pays: United States
ID NLM: 9440159

Informations de publication

Date de publication:
03 2022
Historique:
received: 06 04 2021
revised: 22 06 2021
accepted: 29 06 2021
pubmed: 12 8 2021
medline: 30 4 2022
entrez: 11 8 2021
Statut: ppublish

Résumé

Intracranial aneurysms present in about 3% of the general population and the number of detected aneurysms is continuously rising with the advances in imaging techniques. Intracranial aneurysm rupture carries a high risk of death or permanent disabilities; therefore assessment of the intracranial aneurysm along the entire course is of great clinical importance. Given the outstanding performance of artificial intelligence (AI) in image-based tasks, many AI-based applications have emerged in recent years for the assessment of intracranial aneurysms. In this review we will summarize the state-of-the-art of AI applications in intracranial aneurysms, emphasizing the achievements, and exploring the challenges. We will also discuss the future prospects and potential opportunities. This article provides an updated view of the AI applications in intracranial aneurysms and may act as a basis for guiding the related future works.

Identifiants

pubmed: 34376335
pii: S1076-6332(21)00300-7
doi: 10.1016/j.acra.2021.06.013
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

S201-S214

Informations de copyright

Copyright © 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Auteurs

Osamah Alwalid (O)

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan 430022, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China.

Xi Long (X)

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan 430022, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China.

Mingfei Xie (M)

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan 430022, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China.

Ping Han (P)

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan 430022, China; Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China. Electronic address: cjr.hanping@vip.163.com.

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Classifications MeSH