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Variational-based segmentation of bio-pores in tomographic images

Variational-based segmentation of bio-pores in tomographic images
Variational-based segmentation of bio-pores in tomographic images
X-ray computed tomography (CT) combined with a quantitative analysis of the resulting volume images is a fruitful technique in soil science. However the variations in X-ray attenuation due to different soil components keep the segmentation of single components within these highly heterogeneous samples a challenging problem. Particularly demanding are bio-pores due to their elongated shape and the low gray value difference to the surrounding soil structure. Recently variational models in connection with algorithms from convex optimization were successfully applied for image segmentation. In this paper we apply these methods for the first time for the segmentation of bio-pores in CT images of soil samples. We introduce a novel convex model which enforces smooth boundaries of bio-pores and takes the varying attenuation values in the depth into account. Segmentation results are reported for different real-world 3D data sets as well as for simulated data. These results are compared with two gray value thresholding methods, namely indicator kriging and a global thresholding procedure, and with a morphological approach. Pros and cons of the methods are assessed by considering geometric features of the segmented bio-pore systems. The variational approach features well-connected smooth pores while not detecting smaller or shallower pores. This is an advantage in cases where the main bio-pores network is of interest and where infillings, e.g., excrements of earthworms, would result in losing pore connections as observed for the other thresholding methods.
3D image segmentation, Bio-pores, Gray value thresholding, Morphological segmentation, Root system, Total variation minimization, Variational segmentation
0098-3004
1-8
Bauer, Benjamin
f232b757-99e3-455a-9437-0fb4776008b7
Cai, Xiaohao
de483445-45e9-4b21-a4e8-b0427fc72cee
Peth, Stephan
07a6fd6c-f7db-4e3f-83b0-1112de9eed5d
Schladitz, Katja
416be780-371c-48bc-b5f8-698d8d4585fc
Steidl, Gabriele
c61576e3-9691-455d-bf74-7014841fb0de
Bauer, Benjamin
f232b757-99e3-455a-9437-0fb4776008b7
Cai, Xiaohao
de483445-45e9-4b21-a4e8-b0427fc72cee
Peth, Stephan
07a6fd6c-f7db-4e3f-83b0-1112de9eed5d
Schladitz, Katja
416be780-371c-48bc-b5f8-698d8d4585fc
Steidl, Gabriele
c61576e3-9691-455d-bf74-7014841fb0de

Bauer, Benjamin, Cai, Xiaohao, Peth, Stephan, Schladitz, Katja and Steidl, Gabriele (2017) Variational-based segmentation of bio-pores in tomographic images. Computers and Geosciences, 98, 1-8. (doi:10.1016/j.cageo.2016.09.013).

Record type: Article

Abstract

X-ray computed tomography (CT) combined with a quantitative analysis of the resulting volume images is a fruitful technique in soil science. However the variations in X-ray attenuation due to different soil components keep the segmentation of single components within these highly heterogeneous samples a challenging problem. Particularly demanding are bio-pores due to their elongated shape and the low gray value difference to the surrounding soil structure. Recently variational models in connection with algorithms from convex optimization were successfully applied for image segmentation. In this paper we apply these methods for the first time for the segmentation of bio-pores in CT images of soil samples. We introduce a novel convex model which enforces smooth boundaries of bio-pores and takes the varying attenuation values in the depth into account. Segmentation results are reported for different real-world 3D data sets as well as for simulated data. These results are compared with two gray value thresholding methods, namely indicator kriging and a global thresholding procedure, and with a morphological approach. Pros and cons of the methods are assessed by considering geometric features of the segmented bio-pore systems. The variational approach features well-connected smooth pores while not detecting smaller or shallower pores. This is an advantage in cases where the main bio-pores network is of interest and where infillings, e.g., excrements of earthworms, would result in losing pore connections as observed for the other thresholding methods.

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More information

Accepted/In Press date: 30 September 2016
e-pub ahead of print date: 3 October 2016
Published date: 1 January 2017
Keywords: 3D image segmentation, Bio-pores, Gray value thresholding, Morphological segmentation, Root system, Total variation minimization, Variational segmentation

Identifiers

Local EPrints ID: 438767
URI: http://eprints.soton.ac.uk/id/eprint/438767
ISSN: 0098-3004
PURE UUID: 079a3ccf-2872-4b0a-b53d-689fcdddcac3

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Date deposited: 24 Mar 2020 17:30
Last modified: 19 May 2020 17:03

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Contributors

Author: Benjamin Bauer
Author: Xiaohao Cai
Author: Stephan Peth
Author: Katja Schladitz
Author: Gabriele Steidl

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