Beare Richard, Lowekamp Bradley, Yaniv Ziv
Monash University, Department of Medicin, Monash Medical Centre, Clayton, Melbourne, Australia, 3168,
National Institutes of Health, Office of High Performance Computing and Communications, National Library of Medicine, 8600 Rockville Pike, Bethesda, MD, 20894, United States of America,
J Stat Softw. 2018 Aug;86. doi: 10.18637/jss.v086.i08. Epub 2018 Sep 4.
Many types of medical and scientific experiments acquire raw data in the form of images. Various forms of image processing and image analysis are used to transform the raw image data into quantitative measures that are the basis of subsequent statistical analysis. In this article we describe the R package. is a simplified interface to the insight segmentation and registration toolkit (). is an open source C++ toolkit that has been actively developed over the past 18 years and is widely used by the medical image analysis community. provides packages for many interpreter environments, including R. Currently, it includes several hundred classes for image analysis including a wide range of image input and output, filtering operations, and higher level components for segmentation and registration. Using , development of complex combinations of image and statistical analysis procedures is feasible. This article includes several examples of computational image analysis tasks implemented using , including spherical marker localization, multi-modal image registration, segmentation evaluation, and cell image analysis.
许多类型的医学和科学实验以图像的形式获取原始数据。各种形式的图像处理和图像分析被用于将原始图像数据转换为定量测量值，这些测量值是后续统计分析的基础。在本文中，我们描述了R包。它是洞察分割与配准工具包（ITK）的简化接口。ITK是一个开源的C++工具包，在过去18年中一直在积极开发，并且被医学图像分析社区广泛使用。ITK为许多解释器环境提供了包，包括R。目前，它包括数百个用于图像分析的类，包括广泛的图像输入和输出、滤波操作以及用于分割和配准的高级组件。使用ITK，可以实现复杂的图像和统计分析程序组合。本文包括几个使用ITK实现的计算图像分析任务示例，包括球形标记定位、多模态图像配准、分割评估和细胞图像分析。
