无线电技术
工作流程
人工智能
医学
人工智能应用
领域(数学)
计算机科学
放射科
医学物理学
机器学习
数据库
数学
纯数学
作者
Michaela Cellina,Giovanni Irmici,Gianmarco Della Pepa,Maurizio Cè,Vittoria Chiarpenello,Marco Alì,Sergio Papa,Gianpaolo Carrafiello
标识
DOI:10.1615/critrevoncog.2023051084
摘要
Radiomics, the extraction and analysis of quantitative features from medical images, has emerged as a promising field in radiology with the potential to revolutionize the diagnosis and management of renal lesions. This comprehensive review explores the radiomics workflow, including image acquisition, feature extraction, selection, and classification, and highlights its application in differentiating between benign and malignant renal lesions. The integration of radiomics with artificial intelligence (AI) techniques, such as machine learning and deep learning, can help patientsâ management and allow the planning of the appropriate treatments. AI models have shown remarkable accuracy in predicting tumor aggressiveness, treatment response, and patient outcomes. This review provides insights into the current state of radiomics and AI in renal lesion assessment and outlines future directions for research in this rapidly evolving field.
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