dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM
dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM
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DOI：
10.1158/0008-5472.can-17-0336
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发表时间：
2017-11-01
期刊：
影响因子：
11.2
通讯作者：
Fedorov, Andriy
中科院分区：
文献类型：
--
作者：
Herz, Christian;Fillion-Robin, Jean-Christophe;Fedorov, Andriy
临床图像数据的定量分析是一个活跃的研究领域，有望实现精确医学、治疗反应的早期评估和疾病的客观表征。互操作性、数据共享和挖掘结果数据的能力越来越重要，因为提出的定量分析方法的数量呈爆炸性增长。医学数字成像和通信（DICOM）标准被广泛用于放射学中的图像和元数据。dcmqi（DICOM for Quantitative Imaging）是一个免费的开源库，用于将存储在常用研究格式中的数据转换为标准DICOM表示。dcmqi源代码是在BSD风格的许可证下分发的。它可以作为预编译的二进制包免费提供给每个主要的操作系统，作为Docker镜像，以及作为3D Slicer的扩展。安装和使用说明在GitHub存储库https://github.com/qiicr/dcmqi中提供。(C)2017年AACR。
Quantitative analysis of clinical image data is an active area of research that holds promise for precision medicine, early assessment of treatment response, and objective characterization of the disease. Interoperability, data sharing, and the ability to mine the resulting data are of increasing importance, given the explosive growth in the number of quantitative analysis methods being proposed. The Digital Imaging and Communications in Medicine (DICOM) standard is widely adopted for image and metadata in radiology. dcmqi (DICOM for Quantitative Imaging) is a free, open source library that implements conversion of the data stored in commonly used research formats into the standard DICOM representation. dcmqi source code is distributed under BSD-style license. It is freely available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer. Installation and usage instructions are provided in the GitHub repository at https://github.com/qiicr/dcmqi. (C) 2017 AACR.