影像组学运用中的常用工具与方法

Common tools and methods in the application of radiomics

CT、MRI的出现使医学图像分析成为可能,但仅局限于评估感兴趣区的位置、大小、密度以及其他肉眼可见的特点。随着人工智能技术的发展,影像组学的出现为实现精准医疗提供了新的机遇。影像组学通过提取大通量的医学图像特征,基于机器学习实现疾病的分类、预测和评估,从而量化揭示医学影像内部深层次的信息,为临床决策提供了更为可靠的依据。但是,由于我国影像科医师缺乏工科背景,对于影像组学实现流程中常用的工具和方法不熟悉,限制了其在临床上的广泛应用。本文通过对影像组学流程中的常用工具和方法进行综述,为影像科医师更好的使用影像组学分析方法提供参考。

The emergence of CT and MRI makes medical image analysis possible, but it is limited to evaluate the location, size, density and other characteristics of the region of interest. With the development of artificial intelligence technology, the emergence of radiomics provides a new opportunity for the realization of precision medicine. Through the high-throughput extraction of medical image features, radiomics realizes the classification, prediction and evaluation of diseases based on machine learning, so as to quantitatively reveal the deep-seated information in medical images and provide a more reliable basis for clinical decision-making. However, due to the lack of engineering background of imaging doctors in our country, they are not familiar with the tools and methods commonly used in the implementation process of radiomics, which limits its wide application in clinical practice. This paper summarizes the common tools and methods in the process of radiomics, so as to provide reference for imaging doctors to make better use of imaging analysis methods.