无线电技术
工作流程
基因组学
医学影像学
放射基因组学
精密医学
数据科学
计算生物学
医学物理学
医学
计算机科学
人工智能
病理
生物
基因组
基因
生物化学
数据库
作者
Shiva M. Singh,Bahram Mohajer,Shane A. Wells,Tushar Garg,Kate Hanneman,Takashi Takahashi,Omran AlDandan,Morgan P. McBee,A. Jawahar
标识
DOI:10.1016/j.acra.2024.01.024
摘要
Radiomics uses advanced mathematical analysis of pixel-level information from radiologic images to extract existing information in traditional imaging algorithms. It is intended to find imaging biomarkers related to the genomics of tumors or disease patterns that improve medical care by advanced detection of tumor response patterns in tumors and to assess prognosis. Radiomics expands the paradigm of medical imaging to help with diagnosis, management of diseases and prognostication, leveraging image features by extracting information that can be used as imaging biomarkers to predict prognosis and response to treatment. Radiogenomics is an emerging area in radiomics that investigates the association between imaging characteristics and gene expression profiles. There are an increasing number of research publications using different radiomics approaches without a clear consensus on which method works best. We aim to describe the workflow of radiomics along with a guide of what to expect when starting a radiomics-based research project.
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