Dillman Jonathan R, Somasundaram Elan, Brady Samuel L, He Lili
Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA.
Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Pediatr Radiol. 2022 Oct;52(11):2139-2148. doi: 10.1007/s00247-021-05057-0. Epub 2021 Apr 12.
Artificial intelligence (AI) uses computers to mimic cognitive functions of the human brain, allowing inferences to be made from generally large datasets. Traditional machine learning (e.g., decision tree analysis, support vector machines) and deep learning (e.g., convolutional neural networks) are two commonly employed AI approaches both outside and within the field of medicine. Such techniques can be used to evaluate medical images for the purposes of automated detection and segmentation, classification tasks (including diagnosis, lesion or tissue characterization, and prediction), and image reconstruction. In this review article we highlight recent literature describing current and emerging AI methods applied to abdominal imaging (e.g., CT, MRI and US) and suggest potential future applications of AI in the pediatric population.
人工智能(AI)利用计算机来模拟人类大脑的认知功能,从而能够从通常规模较大的数据集中进行推理。传统机器学习(例如决策树分析、支持向量机)和深度学习(例如卷积神经网络)是医学领域内外常用的两种人工智能方法。这些技术可用于评估医学图像,以实现自动检测与分割、分类任务(包括诊断、病变或组织特征描述以及预测)和图像重建。在这篇综述文章中,我们重点介绍了描述当前以及新兴的应用于腹部成像(例如CT、MRI和超声)的人工智能方法的近期文献,并提出了人工智能在儿科人群中的潜在未来应用。