无线电技术
工作流程
计算机科学
人工智能
医学
领域(数学)
降维
特征选择
机器学习
数据挖掘
医学物理学
数学
数据库
纯数学
作者
Marius E. Mayerhoefer,Andrzej Materka,Georg Langs,Ida Häggström,Piotr M. Szczypiński,Peter Gibbs,Gary Cook
标识
DOI:10.2967/jnumed.118.222893
摘要
Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics—the so-called radiomic features—within medical images. Radiomic features capture tissue and lesion characteristics such as heterogeneity and shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for clinical problem solving. The goal of this continuing education article is to provide an introduction to the field, covering the basic radiomics workflow: feature calculation and selection, dimensionality reduction, and data processing. Potential clinical applications in nuclear medicine that include PET radiomics-based prediction of treatment response and survival will be discussed. Current limitations of radiomics, such as sensitivity to acquisition parameter variations, and common pitfalls will also be covered.
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