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影像信息学:25年的进展

Imaging Informatics: 25 Years of Progress.

作者信息

Agrawal J P, Erickson B J, Kahn C E

机构信息

Charles E. Kahn, Jr., Department of Radiology, 3400 Spruce Street, 1 Silverstein, Philadelphia, PA 19104, USA, E-mail:

出版信息

Yearb Med Inform. 2016 Jun 30;Suppl 1(Suppl 1):S23-31. doi: 10.15265/IYS-2016-s004.

Abstract

The science and applications of informatics in medical imaging have advanced dramatically in the past 25 years. This article provides a selective overview of key developments in medical imaging informatics. Advances in standards and technologies for compression and transmission of digital images have enabled Picture Archiving and Communications Systems (PACS) and teleradiology. Research in speech recognition, structured reporting, ontologies, and natural language processing has improved the ability to generate and analyze the reports of imaging procedures. Informatics has provided tools to address workflow and ergonomic issues engendered by the growing volume of medical image information. Research in computeraided detection and diagnosis of abnormalities in medical images has opened new avenues to improve patient care. The growing number of medical-imaging examinations and their large volumes of information create a natural platform for "big data" analytics, particularly when joined with high-dimensional genomic data. Radiogenomics investigates relationships between a disease's genetic and gene-expression characteristics and its imaging phenotype; this emerging field promises to help us better understand disease biology, prognosis, and treatment options. The next 25 years offer remarkable opportunities for informatics and medical imaging together to lead to further advances in both disciplines and to improve health.

摘要

在过去25年里,医学成像信息学的科学与应用取得了巨大进展。本文对医学成像信息学的关键发展进行了选择性概述。数字图像压缩与传输的标准及技术进步催生了图像存档与通信系统(PACS)和远程放射学。语音识别、结构化报告、本体论及自然语言处理方面的研究提高了生成和分析成像检查报告的能力。信息学提供了工具,以解决因医学图像信息量不断增加而产生的工作流程和人体工程学问题。医学图像中异常情况的计算机辅助检测与诊断研究为改善患者护理开辟了新途径。医学成像检查数量的不断增加及其海量信息为“大数据”分析创造了天然平台,尤其是当与高维基因组数据相结合时。放射基因组学研究疾病的遗传和基因表达特征与其成像表型之间的关系;这一新兴领域有望帮助我们更好地理解疾病生物学、预后及治疗选择。未来25年为信息学和医学成像共同引领这两个学科的进一步发展及改善健康状况提供了绝佳机遇。

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