Analysis of microtomographic images of porous heterogeneous materials: Dissertation

Research output: ThesisDissertationCollection of Articles

Abstract

In this work, we study the phases of image processing chain of microtomographic imag- ing in order to obtain reliable results while optimizing the time spent on denoising and segmentation. We consider that the decisions made at the early phases of the processing chain are most important and the selection made there essentially determine the overall quality of imaging process. We also compare here various denoising method qualita- tively, however, we think that the pure noise removal ability is not the only requirement for noise removal in microtomographic images. By proper denoising we can affect selec- tion of segmentation methods and, thus, also the quality of the analysis. Additionally, at the end, we also review the image segmentation and analysis methods commonly used in microtomographic imaging.
Original languageEnglish
QualificationDoctor Degree
Awarding Institution
  • University of Jyväskylä
Supervisors/Advisors
  • Kärkkäinen, Tommi, Supervisor, External person
  • Timonen, Jussi, Supervisor, External person
  • Valjus, Kirsi, Supervisor, External person
Award date16 Dec 2015
Publisher
Print ISBNs978-951-39-6445-0
Publication statusPublished - 2015
MoE publication typeG5 Doctoral dissertation (article)

Fingerprint

Imaging techniques
Image segmentation
Image analysis
Image processing
Processing

Keywords

  • tietokonetomografia
  • materiaalitutkimus
  • huokoisuus
  • kohina
  • tomografia
  • kuvantaminen
  • kuvankäsittely
  • segmentointi
  • 3D-mallinnus
  • röntgentutkimus

Cite this

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title = "Analysis of microtomographic images of porous heterogeneous materials: Dissertation",
abstract = "In this work, we study the phases of image processing chain of microtomographic imag- ing in order to obtain reliable results while optimizing the time spent on denoising and segmentation. We consider that the decisions made at the early phases of the processing chain are most important and the selection made there essentially determine the overall quality of imaging process. We also compare here various denoising method qualita- tively, however, we think that the pure noise removal ability is not the only requirement for noise removal in microtomographic images. By proper denoising we can affect selec- tion of segmentation methods and, thus, also the quality of the analysis. Additionally, at the end, we also review the image segmentation and analysis methods commonly used in microtomographic imaging.",
keywords = "tietokonetomografia, materiaalitutkimus, huokoisuus, kohina, tomografia, kuvantaminen, kuvank{\"a}sittely, segmentointi, 3D-mallinnus, r{\"o}ntgentutkimus",
author = "Tuomas Turpeinen",
year = "2015",
language = "English",
isbn = "978-951-39-6445-0",
series = "Jyv{\"a}skyl{\"a} studies in computing",
publisher = "University of Jyv{\"a}skyl{\"a}",
number = "230",
address = "Finland",
school = "University of Jyv{\"a}skyl{\"a}",

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Analysis of microtomographic images of porous heterogeneous materials : Dissertation. / Turpeinen, Tuomas.

University of Jyväskylä, 2015. 164 p.

Research output: ThesisDissertationCollection of Articles

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