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诊断放射学中的图像质量:放射科医生方法指南。

Image quality in diagnostic radiology: a guide to methodologies for radiologists.

作者信息

Bastos Andréa de Lima, Nogueira Maria do Socorro

机构信息

School of Medicine, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG, Brazil.

Comissão Nacional de Energia Nuclear (CNEN)/Centro de Desenvolvimento da Tecnologia Nuclear (CDTN), Seção de Dosimetria das Radiações (SECDOS), Belo Horizonte, MG, Brazil.

出版信息

Radiol Bras. 2025 Apr 11;58:e20240088. doi: 10.1590/0100-3984.2024.0088-en. eCollection 2025 Jan-Dec.

Abstract

The aim of this article is to provide a comprehensive guide to image quality assessment in diagnostic radiology, emphasizing practical methodologies for radiologists. The goal is to improve diagnostic accuracy and patient care on the basis of the understanding and application of quantitative and qualitative metrics in clinical practice and research. We conducted a review of the literature in the PubMed, Scopus, Web of Science, and Embase databases. The search terms included "image quality in radiology", "quantitative and qualitative assessment", "modulation transfer function", "signal-to-noise ratio", "contrast-to-noise ratio", "radiation dose optimization", and "artificial intelligence in image quality assessment". The review identified the main methodologies for image quality assessment. We analyzed these metrics for their applicability in clinical settings, highlighting their benefits and limitations. In addition, we discuss qualitative methods such as visual assessment, the assessment of contrast/density, and peer review. This guide fills a gap in the literature by providing accessible, practical knowledge for general radiologists. Ongoing research, education, and technological development are essential to advance the field and ensure high standards in radiology practice.

摘要

本文旨在为诊断放射学中的图像质量评估提供全面指南,重点介绍面向放射科医生的实用方法。目标是在临床实践和研究中理解和应用定量与定性指标的基础上,提高诊断准确性和患者护理水平。我们对PubMed、Scopus、Web of Science和Embase数据库中的文献进行了综述。检索词包括“放射学中的图像质量”、“定量和定性评估”、“调制传递函数”、“信噪比”、“对比噪声比”、“辐射剂量优化”以及“图像质量评估中的人工智能”。该综述确定了图像质量评估的主要方法。我们分析了这些指标在临床环境中的适用性,突出了它们的优点和局限性。此外,我们还讨论了定性方法,如视觉评估、对比度/密度评估和同行评审。本指南通过为普通放射科医生提供易于理解的实用知识,填补了文献中的空白。持续的研究、教育和技术发展对于推动该领域发展并确保放射学实践的高标准至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f30d/12013331/e6e5f4a15f6b/rb-58-e20240088-g01.jpg

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