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<p>Radiomics and artificial intelligence (AI) are rapidly evolving, significantly transforming the field of medical imaging. Despite their growing adoption, these technologies remain challenging to approach due to their technical complexity. This review serves as a practical guide for early-career radiologists and researchers seeking to integrate radiomics into their studies. It provides practical insights for clinical and research applications, addressing common challenges, limitations, and future directions in the field. This work offers a structured overview of the essential steps in the radiomics workflow, focusing on concrete aspects of each step, including indicative and practical examples. It covers the main steps such as dataset definition, image acquisition and preprocessing, segmentation, feature extraction and selection, and AI model training and validation. Different methods to be considered are discussed, accompanied by summary diagrams. This review equips readers with the knowledge necessary to approach radiomics and AI in medical imaging from a hands-on research perspective.</p>

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Insights into radiomics: a comprehensive review for beginners

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月12日

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  • Francesco Mariotti,
  • Andrea Agostini,
  • Alessandra Borgheresi,
  • Marzia Marchegiani,
  • Alice Zannotti,
  • Gloria Giacomelli,
  • Luca Pierpaoli,
  • Elisabetta Tola,
  • Elena Galiffa,
  • Andrea Giovagnoni

摘要

Radiomics and artificial intelligence (AI) are rapidly evolving, significantly transforming the field of medical imaging. Despite their growing adoption, these technologies remain challenging to approach due to their technical complexity. This review serves as a practical guide for early-career radiologists and researchers seeking to integrate radiomics into their studies. It provides practical insights for clinical and research applications, addressing common challenges, limitations, and future directions in the field. This work offers a structured overview of the essential steps in the radiomics workflow, focusing on concrete aspects of each step, including indicative and practical examples. It covers the main steps such as dataset definition, image acquisition and preprocessing, segmentation, feature extraction and selection, and AI model training and validation. Different methods to be considered are discussed, accompanied by summary diagrams. This review equips readers with the knowledge necessary to approach radiomics and AI in medical imaging from a hands-on research perspective.