Artificial Intelligence and Deep Learning in Neuroradiology: Exploring the New Frontier

被引：43
作者：
Kaka, Hussam [1 ]
Zhang, Euan [2 ]
Khan, Nazir [2 ]
机构：
[1] McMaster Univ, Dept Radiol, 1200 Main St West, Hamilton, ON L8N 3Z5, Canada
[2] McMaster Univ, Hamilton Gen Hosp, Dept Radiol, Hamilton, ON, Canada
来源：
CANADIAN ASSOCIATION OF RADIOLOGISTS JOURNAL-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES | 2021年 / 72卷 / 01期
关键词：
artificial; intelligence; deep; learning; neuroradiology; CONVOLUTIONAL NEURAL-NETWORKS; ANEURYSMS; SCLEROSIS;
D O I：
10.1177/0846537120954293
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
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.
引用
收藏
页码：35 / 44
页数：10
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