Noise Patterns in industrial Micro Computed Tomography

Table of Contents

1 Introduction

1.1 The Natural History Museum London (NHM)

1.1.1 The beginning of the British Museum (NHM London)

1.1.2 NHM in the 21st Century

1.2 Computed Tomography(CT) – Introduction

1.2.1 Industrial Computed Tomography

1.2.2 Micro-CT

1.2.3 Image J

1.3 Noise/Artefacts

1.3.1 Artefacts

1.3.1.1 Motion Artefacts

1.3.1.2 Ring Artefacts

1.3.1.3 Metal Artefacts

1.3.1.4 Beam Hardening Artefacts

1.3.1.5 Partial Volume Artefacts

1.3.1.6 Other artefacts

1.3.2 Noise

1.4 Filters

1.4.1 Reasons for using a digital filter

1.4.2 High-pass Filters

1.4.3 Low-pass Filters

1.4.4 Kalman Stack Filter

1.4.5 Gaussian blur Filter

1.4.6 Kuwahara Filter

2 Project Assignment: Analysing noise pattern in Micro-CT

2.1 Materials and Methods

2.1.1 Metris X-Tek HMX ST 225 CT System

2.1.2 Phantom Design

2.1.3 ImageJ plug-in Code

2.1.3.1 Development of the plug-in

2.1.3.2 Using the Plug-in

2.2 Description of project objectives: Part I, Part II and Part III

2.2.1 Part I: How do scan parameters affect noise?

2.2.2 Part II: What is the best type of noise reduction algorithm for CT?

2.2.3 Part III: How current, exposure and noise affect other?

2.3 Summary and Analysis

2.3.1 Analysing pattern of the noise variation

2.3.2 Optimising parameters for noise reduction

2.3.2.1 Effect of noise reduction filters

2.3.2.2 Comparing the filters

2.3.2.3 Optimum noise reduction algorithm

2.3.2.4 Comparison between Kalman stack filter with the reduction algorithm in CTpro

2.3.3 Analysing current vs. exposure effect

3 Conclusion and future work

3.1 Insight from experiments

3.2 Insights from post-processing

3.3 Suggestions for future work

Objectives and Topics

This work aims to understand and mitigate noise and artefacts in high-resolution micro-computed tomography (micro-CT) imaging. The primary research goal is to optimize scan parameters and evaluate noise reduction algorithms to improve image quality and diagnostic accuracy for biological and mineralogical specimens.

• Optimization of micro-CT scan parameters (voltage, current, exposure).
• Comparative analysis of digital noise reduction algorithms (e.g., Kalman, Gaussian, Kuwahara).
• Investigation of the relationship between current, exposure, and image noise.
• Development of a custom ImageJ plug-in for quantitative noise analysis.
• Evaluation of industrial CT-specific challenges and artefact types.

Excerpt from the Book

Summary of Chapters

1 Introduction: Provides historical background on the Natural History Museum and explains the fundamental principles of CT and micro-CT, including definitions of noise and artefacts.

2 Project Assignment: Analysing noise pattern in Micro-CT: Details the experimental setup, methodologies, and the systematic investigation of scan parameters and digital filtering techniques.

3 Conclusion and future work: Summarizes the key findings regarding optimal scanning parameters and the effectiveness of specific filters, while suggesting further research directions.

Keywords

Micro-CT, Computed Tomography, Image Noise, Artefacts, Digital Filters, Kalman Stack Filter, Gaussian Blur, Kuwahara Filter, ImageJ, Scan Parameters, X-ray Energy, Signal-to-Noise Ratio, Industrial CT, Image Quality, Phantom Design.

Frequently Asked Questions

What is the primary focus of this work?

The work focuses on understanding and reducing noise and artefacts in high-resolution micro-CT imaging to improve quantitative analysis of samples.

What are the central thematic fields?

The central themes include the physics of CT imaging, the classification of noise/artefacts, and the application of post-processing digital filters.

What is the core research goal?

The goal is to determine optimal scan parameters and the most effective noise reduction algorithms for industrial micro-CT systems.

Which scientific methodology is employed?

The research uses experimental scanning of a glass-bead/flour phantom, followed by quantitative analysis using a custom-developed ImageJ plug-in.

What topics are covered in the main section?

The main part covers the technical details of the X-Tek CT system, the design of the phantom, and the comparative analysis of various noise reduction algorithms.

Which keywords characterize this work?

Key terms include Micro-CT, Noise Reduction, Kalman Stack Filter, Artefacts, ImageJ, and X-ray parameter optimization.

What is the difference between noise and artefacts in this context?

According to the text, artefacts are inherent to the X-ray system, whereas noise is considered an external influence affecting the signal.

What did the analysis of the Kalman Stack Filter reveal?

The analysis indicated that the Kalman Stack Filter provides the best performance for noise reduction, outperforming the in-built CTPro noise reduction algorithm.

What is the significance of the "critical current" mentioned in the results?

The study identified a critical current of 60 μA; deviations from this point in either direction were found to potentially increase standard deviation and noise levels.