MRI影像组学及深度学习在直肠癌中的研究进展
Research Progress of Radiomics and Deep Learning in Rectal Cancer
彭琳 1王冬青 1庄子健 1陈星池 1薛靖 1张礼荣1
作者信息
- 1. 江苏大学附属医院医学影像科(江苏镇江 212000)
- 折叠
摘要
磁共振成像(magnetic resonance imaging,MRI)目前已广泛应用于直肠癌的分期、疗效评估,甚至可用于病理指标及基因突变的预测.基于人工智能领域的影像组学和深度学习等方法从MRI中挖掘病灶深层次信息以进一步分析,可为临床个体化诊疗提供新的依据.目前,大量直肠癌MRI影像组学或深度学习的研究显示出潜在的临床应用价值.本文总结了近年来MRI影像组学及深度学习在直肠癌诊疗中的研究进展,为后续研究提供参考.
Abstract
Magnetic resonance imaging(MRI)has been widely performed in the staging and efficacy assessment of rectal cancer,and can even be used for the prediction of pathological indicators and gene mutations.To provide a new basis for clinical individualized diagnosis and treatment,methods such as radiomics and deep learning based on the field of artificial intelligence to mine deep information of lesions from MRI for further analysis.Currently,a large number of studies on MRI radiomics or deep learning for rectal cancer have shown potential clinical applications.In this paper,we summarize the research progress of MRI radiomics and deep learning in rectal cancer diagnosis and treatment in recent years,aiming to provide reference for subsequent research.
关键词
影像组学/深度学习/直肠癌/磁共振成像/人工智能Key words
Radiomics/Deep Learning/Rectal Cancer/Magnetic Resonance imaging/Artificial Intelligence引用本文复制引用
基金项目
镇江"金山英才"高层次领军人才培养计划(169工程)培养对象科研项目(第六期)(YLJ202111)
出版年
2024
NETL
NSTL
维普
万方数据