人工智能在肌肉骨骼成像中的解释性应用:概念、当前实践和未来方向

Teresa T. Martin-Carreras, Hongming Li, Po-Hao Chen
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引用次数: 3

摘要

:人工智能有望对放射学领域产生广泛影响,并有可能影响图像解释的各个方面。近几十年来,计算能力的重大进步,加上大型数据存储或“大数据”的可用性和算法民主化,彻底改变了人工智能和机器学习(ML)。利用这些技术进步的研究应用正在蓬勃发展,预计其采用率将继续快速上升。虽然人工智能和ML影响了成像价值链的许多组成部分,但本文的目的是讨论该技术在肌肉骨骼(MSK)放射学方面的解释性使用。这篇综述对人工智能和ML概念进行了全面介绍,并强调了这些发展在MSK放射学中的主要前景、挑战和预期的未来应用。AI和ML在图像解释方面的进步可以提高MSK放射科医生为患者、转诊临床医生和组织提供的价值,方法是提高诊断准确性,同时减少周转时间,增强图像处理和定量分析,并可能改善患者的预后。MSK临床医生和研究人员对这些过程的熟悉对于这些新技术在临床实践中的改进和实施至关重要。现在接受这些技术的放射科、诊所和从业者将非常适合在不久的将来领导我们领域的这一有影响力的变革。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interpretative applications of artificial intelligence in musculoskeletal imaging: concepts, current practice, and future directions
: Artificial intelligence (AI) promises wide-reaching impacts on the field of radiology, and has the potential to influence every aspect of image interpretation. In recent decades, significant advancements in computing power, combined with the availability of large data stores or “Big Data” and algorithm democratization have revolutionized AI and machine learning (ML). Research applications utilizing these technological advancements are booming, and their adoption is expected to continue to rise at a rapid pace. While AI and ML have impacted many components of the imaging value chain, the purpose of this article is to discuss interpretative uses of the technology as it relates to musculoskeletal (MSK) radiology. This review provides a general introduction to AI and ML concepts, and highlights the major promises, challenges, and anticipated future applications of these developments in MSK radiology. AI and ML advances for image interpretation can increase the value that MSK radiologists provide to their patients, referring clinicians, and organizations by increasing diagnostic accuracy while decreasing turnaround times, enhancing image processing and quantitative analysis, and by potentially improving patient outcomes. Familiarity with these processes among MSK clinicians and researchers will be paramount to the improvement and implementation of these new techniques into the clinical practice. Radiology departments, practices and practitioners who embrace these technologies now will be well-suited to lead this influential change in our field in the near future.
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