Abstract

X-ray computed tomography (CT) is a non-destructive imaging technique that provides three-dimensional (3D) visualisation and high-resolution quantitative data in the form of CT numbers. CT numbers are derived from the X-ray energy, effective atomic number and density of the analysed material. The sensitivity of the CT number to changes in material density means that it can be used to identify facies changes within sediment cores by detecting downcore shifts in sediment properties, and to quantify skeletal linear extension rates and internal biological erosion from coral cores. Here we present two algorithms to analyse CT scan images for geoscience research and package them within an open-source MATLAB application (Core-CT) that is freely available at GitHub (https://github.com/yuting-yan/Core-CT). The first algorithm computes CT numbers from a user-defined region of interest to identify boundaries of density change (e.g., sedimentary facies, laminations, coral growth bands). The second algorithm segments regions with major density contrast (e.g., internal void space or biogenic material) and provides 3D geometrical measurements of these irregularities. The versatility of Core-CT for geoscience is demonstrated for a range of environmental settings using both lake and marine sediment cores (Chile and Singapore) and coral cores (Red Sea). Core-CT analysis of sediment cores shows the application is able to: (1) distinguish episodic tsunami deposits from lacustrine sediments, (2) generate rapid and detailed measurement of varved sediments, and (3) identify sedimentary facies from an unsplit marine sediment core. When applied to coral cores, Core-CT can measure skeletal linear extension of annual growth bands and provide 3D visualisation and volumetric quantification of internal bioerosion cavities. Other potential applications of Core-CT include the identification of cryptotephra in sediment cores, or laminations in speleothem samples.

Highlights

  • Computed Tomography (CT) is a non-destructive method used for creating detailed imagery that has been widely applied to many geoscience-related fields (Cnudde and Boone, 2013; Ketcham and Carlson, 2001)

  • We developed an algorithm that allows users to define a region of interest (ROI) within the computed tomography (CT) scan images, from which a continuous CT profile can be obtained

  • Core-CT was used to detect paleotsunami deposits preserved within the sedimentary record by constructing a mean CT number profile of lacustrine cores collected from Lake Huelde, Chile (Kempf et al, 2015, 2017)

Read more

Summary

Introduction

Computed Tomography (CT) is a non-destructive method used for creating detailed imagery that has been widely applied to many geoscience-related fields (Cnudde and Boone, 2013; Ketcham and Carlson, 2001) This imaging technique uses mono-energetic X-rays to produce high-resolution cross-sectional images, which are stacked together to construct complex three-dimensional (3D) volumes (e.g., Duliu, 1999; Ketcham and Carlson, 2001). As X-ray attenuation is dependent on density, voxel values can be used to make sub-millimetre scale measurements of bulk density in a non-destructive way (Duchesne et al, 2009; Orsi and Anderson, 1999; Toscano et al, 2018)

Geoscience applications of CT scanning
Challenges of using CT data
Core-CT
Quantitative data in CT scan images
Method 1: constructing mean CT number profiles from ROI
Cropping of ROI
Identifying change points in CT numbers downcore
Method 2: localized CT number profile
Image and volume segmentation of identified regions
Implementation
Applications of Core-CT in geoscience investigations
Case study 2: identification of sedimentary units in unsplit sediment cores
Conclusions
Computer code availability
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call