x射线图像分析的人工智能解决方案。

Scott J Adams, Robert D E Henderson, Xin Yi, Paul Babyn
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引用次数: 26

摘要

人工智能(AI)为放射科医生提供了改善护理质量和提高放射学在患者护理和人口健康方面的价值的关键机会。人工智能在辅助常规x光片(x射线图像)分类和解释方面的潜在机会尤其重要,因为x光片是大多数放射科最常见的影像学检查。在过去几年中,用于胸部和肌肉骨骼(MSK) x光片分析的人工智能算法的开发取得了实质性进展,深度学习现在是图像分析的主要方法。大量的公共和专有图像数据集已经被编译,并帮助开发了用于分析x光片的人工智能算法,其中许多算法在特定的、集中的任务中显示出与放射科医生相当的准确性。本文描述了(1)用于x线片分析的人工智能解决方案开发的基础,(2)目前用于辅助胸部x线片和MSK x线片分类和解释的人工智能解决方案,(3)人工智能辅助x线片相关非解释性任务的机会,以及(4)放射学实践选择用于x线片分析的人工智能解决方案并将其集成到现有IT系统中的考虑。尽管跨模式的综合人工智能解决方案尚未开发,但机构可以开始选择和整合重点解决方案,以提高效率,提高质量和患者安全,并为患者增加价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Solutions for Analysis of X-ray Images.

Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conventional radiographs (X-ray images) is particularly significant, as radiographs are the most common imaging examinations performed in most radiology departments. Substantial progress has been made in the past few years in the development of AI algorithms for analysis of chest and musculoskeletal (MSK) radiographs, with deep learning now the dominant approach for image analysis. Large public and proprietary image data sets have been compiled and have aided the development of AI algorithms for analysis of radiographs, many of which demonstrate accuracy equivalent to radiologists for specific, focused tasks. This article describes (1) the basis for the development of AI solutions for radiograph analysis, (2) current AI solutions to aid in the triage and interpretation of chest radiographs and MSK radiographs, (3) opportunities for AI to aid in noninterpretive tasks related to radiographs, and (4) considerations for radiology practices selecting AI solutions for radiograph analysis and integrating them into existing IT systems. Although comprehensive AI solutions across modalities have yet to be developed, institutions can begin to select and integrate focused solutions which increase efficiency, increase quality and patient safety, and add value for their patients.

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