Technical Note: Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics research
Technical Note: Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics research
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DOI：
10.1002/mp.13046
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发表时间：
2018-08-01
期刊：
影响因子：
3.8
通讯作者：
Deasy, Joseph O.
中科院分区：
文献类型：
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作者：
Apte, Aditya P.;Iyer, Aditi;Deasy, Joseph O.
放射组学是一个正在发展的图像定量领域，但它缺乏稳定和高质量的软件系统。我们扩展了放射学研究的计算环境（CERR）的功能，以创建一个全面的，开源的，基于MATLAB的软件平台，重点是放射组学研究的再现性，速度和临床整合。和可视化。CERR允许放射组学特征的批量计算和可视化，并为放射组学元数据提供用户友好的数据结构。所有放射组学计算都是矢量化的，以提高速度。此外，还提供了一个测试套件，用于重建并与使用其他软件平台（如Insight Toolkit（ITK）和PyRadiomics）计算的放射组学特征进行比较。根据图像生物标志物标准化倡议定义的标准评价CERR。CERR的放射组学特征计算与临床使用的MIM软件使用其MATLAB（（R））应用程序编程接口集成。计算密集型Haralick纹理的矩阵公式产生的速度上级ITK 4.12中的实现。对于离散成32个bin的图像，CERR实现了比ITK快3.5倍的加速。CERR测试套件使编程错误的成功识别，以及真正的差异，在放射组学的定义和计算在整个software packages tested.ConclusionThe CERR的放射组学功能是全面的，开源的，快速的，使其成为一个有吸引力的平台，开发和探索放射组学签名跨机构。从各种放射组学实施中进行选择并与临床工作流程集成的能力使得CERR对于回顾性和前瞻性研究分析都很有用。
PurposeRadiomics is a growing field of image quantitation, but it lacks stable and high-quality software systems. We extended the capabilities of the Computational Environment for Radiological Research (CERR) to create a comprehensive, open-source, MATLAB-based software platform with an emphasis on reproducibility, speed, and clinical integration of radiomics research.MethodThe radiomics tools in CERR were designed specifically to quantitate medical images in combination with CERR's core functionalities of radiological data import, transformation, management, image segmentation, and visualization. CERR allows for batch calculation and visualization of radiomics features, and provides a user-friendly data structure for radiomics metadata. All radiomics computations are vectorized for speed. Additionally, a test suite is provided for reconstruction and comparison with radiomics features computed using other software platforms such as the Insight Toolkit (ITK) and PyRadiomics. CERR was evaluated according to the standards defined by the Image Biomarker Standardization Initiative. CERR's radiomics feature calculation was integrated with the clinically used MIM software using its MATLAB((R)) application programming interface.ResultsThe CERR provides a comprehensive computational platform for radiomics analysis. Matrix formulations for the compute-intensive Haralick texture resulted in speeds that are superior to the implementation in ITK 4.12. For an image discretized into 32 bins, CERR achieved a speedup of 3.5 times over ITK. The CERR test suite enabled the successful identification of programming errors as well as genuine differences in radiomics definitions and calculations across the software packages tested.ConclusionThe CERR's radiomics capabilities are comprehensive, open-source, and fast, making it an attractive platform for developing and exploring radiomics signatures across institutions. The ability to both choose from a wide variety of radiomics implementations and to integrate with a clinical workflow makes CERR useful for retrospective as well as prospective research analyses.