Analysis of multiple resolution μ-CT image sets for pore-size distribution estimation

Baran Aydogan; Markus Hannula; Niko Moritz; Erkki Levänen; Jari Hyttinen

doi:10.1007/978-3-642-03882-2_334

Analysis of multiple resolution μ-CT image sets for pore-size distribution estimation

Baran Aydogan^*, Markus Hannula, Niko Moritz, Erkki Levänen, Jari Hyttinen

^*Corresponding author for this work

Not published at Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

In this paper we are analyzing multiple μ-CT image sets to estimate pore-size distribution based on minimum visible pore-size at a given resolution. As similar approaches rely strongly on segmentation results, we are evaluating and comparing 5 different thresholding based segmentation approaches. The application of the method is demonstrated on Al₂O₃ bulk imaged at 7 different resolutions.

Original language	English
Title of host publication	World Congress on Medical Physics and Biomedical Engineering
Subtitle of host publication	Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Pages	1261-1264
Number of pages	4
Volume	25
Edition	4
DOIs	https://doi.org/10.1007/978-3-642-03882-2_334
Publication status	Published - 1 Dec 2009
MoE publication type	A4 Article in a conference publication
Event	World Congress on Medical Physics and Biomedical Engineering - Munich, Germany Duration: 7 Sep 2009 → 12 Sep 2009

Conference

Conference	World Congress on Medical Physics and Biomedical Engineering
Country	Germany
City	Munich
Period	07/09/2009 → 12/09/2009

Keywords

μ-CT image analysis
Pore-size distribution
Segmentation
Thresholding

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Aydogan, B., Hannula, M., Moritz, N., Levänen, E., & Hyttinen, J. (2009). Analysis of multiple resolution μ-CT image sets for pore-size distribution estimation. In World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics (4 ed., Vol. 25, pp. 1261-1264) https://doi.org/10.1007/978-3-642-03882-2_334

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title = "Analysis of multiple resolution μ-CT image sets for pore-size distribution estimation",

abstract = "In this paper we are analyzing multiple μ-CT image sets to estimate pore-size distribution based on minimum visible pore-size at a given resolution. As similar approaches rely strongly on segmentation results, we are evaluating and comparing 5 different thresholding based segmentation approaches. The application of the method is demonstrated on Al2O3 bulk imaged at 7 different resolutions.",

keywords = "μ-CT image analysis, Pore-size distribution, Segmentation, Thresholding",

author = "Baran Aydogan and Markus Hannula and Niko Moritz and Erkki Lev{\"a}nen and Jari Hyttinen",

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doi = "10.1007/978-3-642-03882-2_334",

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Aydogan, B, Hannula, M, Moritz, N, Levänen, E & Hyttinen, J 2009, Analysis of multiple resolution μ-CT image sets for pore-size distribution estimation. in World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4 edn, vol. 25, pp. 1261-1264, World Congress on Medical Physics and Biomedical Engineering, Munich, Germany, 07/09/2009. https://doi.org/10.1007/978-3-642-03882-2_334

Analysis of multiple resolution μ-CT image sets for pore-size distribution estimation. / Aydogan, Baran; Hannula, Markus; Moritz, Niko; Levänen, Erkki; Hyttinen, Jari.

World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. Vol. 25 4. ed. 2009. p. 1261-1264.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AB - In this paper we are analyzing multiple μ-CT image sets to estimate pore-size distribution based on minimum visible pore-size at a given resolution. As similar approaches rely strongly on segmentation results, we are evaluating and comparing 5 different thresholding based segmentation approaches. The application of the method is demonstrated on Al2O3 bulk imaged at 7 different resolutions.

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