摘要
缺血性脑卒中也称为脑梗死,是由复杂原因引起的脑组织供血紊乱,造成梗死部位不可逆性损伤的一种疾病。根据我国第六次人口普查显示,2018年我国约有194万人死于卒中,严重影响我国居民健康。随着我国人口老龄化的不断加剧,预计在未来十几年内,中风将持续影响人类健康。影像学检查方法是确诊疾病和评估预后不可或缺的重要手段。近年来,人工智能(AI)和影像组学(radiomics)广泛应用医疗行业,其中,卷积神经网络(CNN)应用较多,尤其在缺血性脑卒中的影像诊断中体现出明显的优越性,效率远远超于人工阅片。本文基于CT和磁共振的影像组学在缺血性脑卒中的研究进展进行综述。
Ischemic stroke,also known as cerebral infarction,is a disorder impacting the blood supply to the brain tissue due to complex reasons,resulting in irreversible damage to the infarct site.According to China's sixth census,approximately 1.94 million individuals died of a stroke in 2018.With the increasing age of the Chinese population,stroke is expected to continue affecting human health in the coming decade.Imaging examination is an indispensable means to diagnose the disease and evaluate its prognosis.In recent years,artificial intelligence and radiomics have been widely used in the medical industry,among which convolutional neural network is more prevalent.Mainly,it has shown obvious superiority in the imaging diagnosis of ischemic stroke,and its efficiency is far higher than manual film reading.This article reviews the research progress of imaging omics based on computed tomography(CT)and magnetic resonance in ischemic stroke.
作者
王姗
赵建华
WANG Shan;ZHAO Jianhua(Graduate School of Inner Mongolia Medical University,Hohhot 010059,China;Department of Medical Imaging,Inner Mongolia People’s Hospital,Hohhot 010017,China)
出处
《CT理论与应用研究（中英文）》
2024年第1期83-89,共7页
Computerized Tomography Theory and Applications
基金
内蒙古自治区人民医院院内基金(基于深度学习的病毒性肺炎不同临床转归胸部CT评价(2020YN08))
包头医学院研究生教育改革项目(人工智能在放射影像学专业学位研究生教学中的初步应用(BYJSJG202303))
内蒙古医科大学高等教育改革研究项目(“人工智能+教学”模式在医学影像专业教学中的应用探索(NYJXG2023139))
内蒙古医科大学联合项目(基于深度学习和影像组学预测急性缺血性脑卒中发病时间的研究(YKD2023LH088))。
作者简介
王姗,女,内蒙古医科大学放射影像学硕士研究生,主要从事缺血性脑卒中的研究,E-mail:3429873516@qq.com;赵建华,男,内蒙古自治区人民医院影像医学科副主任医师、硕士研究生导师,主要从事影像诊断工作,E-mail:zjh2822yyjh@163.com。
