Computer Tomography (CT) systems are used to produced images that are finding increasing use in medicine and mineralogy as in the Natural History Museum. In order to maximise the system performance, the images or scans, must have high quality.
Ideally, the physical CT system should preserve the image quality. However, in reality,various physical processes degrade the quality of these images, producing noise and artefacts.
The goal of this work is to understand the noise and artefacts in high-resolution imaging application of micro computer tomography (micro-CT). The project specifically lookedat determining:
I. How micro-CT scan parameters be optimised to reduce noise, and
II. Which of the many commonly used noise reduction algorithms produce the best results, and
III. How current and exposure effect each other.
Experiments were carried out to obtain the raw data – images / scans for the study. Theoretical models were then implemented on the raw data to analyse and better understand the noise and artefacts in the images.
This work provides a better understanding of both the fundamental performance (i.e. image quality) of the micro-CT system, and the assessment of user-defined parameters that could be used to optimise the performance of the micro-CT systems.
These contributions will not only save time, money and resources, which will ultimately lead to better image quality (greater accuracy)
Table of contents
Table of Figures
Table of Tables
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 ImageJ
1.3 Noise/Artefacts
1.3.1 Artefacts
1.3.2 Noise
1.4 Filters
1.4.1 Reasons for using a digital filter
1.4.2 High-passFilters
1.4.3 Low-passFilters
1.4.4 Kalman Stack Filter
1.4.5 Gaussian blurFilter
1.4.6 Kuwahara Filter
2 Project Assignment: Analysing noise pattern in Micro-CT
2.1 MaterialsandMethods
2.1.1 Metrls X-Tek HMX ST 225 CT System
2.1.2 Phantom Design
2.1.3 ImageJ plug-in Code
2.2 Description ofproject objectives: Parti, Part II and Part III
2.2.1 Part I: How do scan parameters affect noise?
2.2.2 Part II: Whatis the best type of noise reduction algorithm for CT?
2.2.3 Part III: How current, exposure and noise affect each other?
2.3 Summary and Analysis
2.3.1 Analysing pattern of the noise variation
2.3.2 Optmising parameters for noise reduction
2.3.3 Analysing current vs. exposure effect
3 Conclusionandfuturework
3.1 Insightfrom experiments
3.2 Insights from post-processing
3.3 Suggestionsforfuturework:
AppendixA
Plug-in Code
How to use the Plug-in
References
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