4 Jan 2021

Multi-component analysis of X-ray Computed Tomography datasets

The following videos and training material detail the steps taken to automate the analysis of multiple parts in a single X-ray CT volume.

The automation of post data analysis in X-ray CT is very dependent upon the subject items and scan setup, the open tool kits in Avizo Software allow the software to excel in producing individualized automated analysis routines that would otherwise be very difficult. The open nature of the tool box in Avizo Software also allows users to understand the process involved in each step thus avoiding a black box effect where users are unaware of how the data may have been distorted or changed.

Chapter 1. Data collection and compromising artefacts

Chapter 2. Data preparation

Chapter 3. Pore analysis

Chapter 4. Pore filtering

Chapter 5. Recipe creation and application

Prerequiste: you should be familiar with the recipes concept of Avizo Software. Learn more from the product documentation or our Xtra ressources.

Speaker: Tristan Lowe, PhD, Senior Experimental Officer in X-ray imaging at the Henry Moseley X-ray Imaging Facility, The University of Manchester.

To follow this training, you should be familiar with the basic concepts of Avizo Software such as data loading, interacting with the 3D viewer, connecting modules, etc.

You can download the training material from the Download link.

You can also download a cropped version of the dataset used in this tutorial in order to reproduce it. When loading the data it is important to input the correct dimensions, in the correct unit, in the Image Read Parameters dialog that will open. This can be found in the reconstruction information file. As this file is not available for download here, here is the information: the effective pixel size from the CT scan itself is 15 µm so please make sure to enter the voxel size 15 µm in all directions (see Figure 1 below). The next window (Units Editor) will ask for the correct unit (see Figure 2 below).

Data courtesy of Dr. Shengchuan Wu, Southwest Jiaotong University