Development of Efficient X-Ray CT Image Segmentation Techniques for Quantitative Analysis of Phase Distributions and Flow Processes in Porous Media

开发高效 X 射线 CT 图像分割技术，用于定量分析多孔介质中的相分布和流动过程

• 批准号: 0911242
• 负责人: Markus Tuller
• 金额: $ 24.98万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0911242&HistoricalAwards=false
• 关键词: Development; Efficient; Ray; CT; Image

Development of Efficient X-Ray CT Image Segmentation Techniques for Quantitative Analysis of Phase Distributions and Flow Processes in Porous MediaMarkus Tuller, Pavel Iassonov and Marcel SchaapThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Nondestructive imaging methods such as X-Ray Computed Tomography (CT) yield high-resolution 3 D representations of pore space and fluid distribution within porous materials. Steadily increasing computational capabilities and easier access to industrial and synchrotron X Ray CT facilities have contributed to a recent surge in microporous media research with objectives ranging from theoretical aspects of fluid and interfacial dynamics at the pore-scale to practical applications such as (D)NAPL transport and dissolution. In recent years, significant efforts and resources have been devoted to improve CT technology, micro-scale analysis, and fluid dynamics simulations. However, the development of adequate image segmentation methods for conversion of grayscale CT volumes into a discrete form that permits quantitative characterization of pore space features and subsequent modeling of liquid distribution and flow processes is lacking far behind. A preliminary study revealed that most of the documented segmentation methods that were originally developed for optical character recognition, pattern analysis, or medical research yield vastly different results when applied to X-Ray CT data of porous materials. Furthermore, there is virtually no commercial or open-source software with advanced image segmentation capabilities suitable for automated processing of large CT data sets available.To overcome these shortcomings we will identify the most promising segmentation methods and develop new hybrid algorithms tailored to industrial and synchrotron X-Ray CT data of natural porous media. Lattice Boltzmann simulations within X-Ray CT-derived discretized pore space compared to independently measured hydraulic properties will guide the development process. The generated algorithms will be combined in a user-friendly, stand-alone, and well documented software package and made available to the scientific community.

开发高效 X 射线 CT 图像分割技术，用于定量分析多孔介质中的相分布和流动过程Markus Tuller、Pavel Iassonov 和 Marcel Schaap 该奖项由 2009 年美国复苏和再投资法案（公法 111-5）资助。 X 射线计算机断层扫描 (CT) 等无损成像方法可生成多孔材料内孔隙空间和流体分布的高分辨率 3D 表示。计算能力的稳步提高以及工业和同步加速器 X 射线 CT 设施的更容易使用，最近促进了微孔介质研究的激增，其目标范围从孔隙尺度的流体和界面动力学的理论方面到 (D)NAPL 传输和溶解等实际应用。近年来，人们投入了大量的精力和资源来改进 CT 技术、微尺度分析和流体动力学模拟。然而，将灰度 CT 体积转换为离散形式的适当图像分割方法的开发还远远落后，这种离散形式允许对孔隙空间特征进行定量表征以及随后对液体分布和流动过程进行建模。一项初步研究表明，大多数最初为光学字符识别、模式分析或医学研究而开发的分割方法在应用于多孔材料的 X 射线 CT 数据时会产生截然不同的结果。 此外，几乎没有具有先进图像分割功能的商业或开源软件适合自动处理大型 CT 数据集。为了克服这些缺点，我们将确定最有前途的分割方法，并开发适合天然多孔介质的工业和同步加速器 X 射线 CT 数据的新混合算法。 X 射线 CT 衍生的离散孔隙空间内的格子玻尔兹曼模拟与独立测量的水力特性进行比较，将指导开发过程。 生成的算法将合并在一个用户友好的、独立的、有据可查的软件包中，并提供给科学界。