Variational-based segmentation of bio-pores in tomographic images. (January 2017)
- Record Type:
- Journal Article
- Title:
- Variational-based segmentation of bio-pores in tomographic images. (January 2017)
- Main Title:
- Variational-based segmentation of bio-pores in tomographic images
- Authors:
- Bauer, Benjamin
Cai, Xiaohao
Peth, Stephan
Schladitz, Katja
Steidl, Gabriele - Abstract:
- 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,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. Abstract : Highlights: A variational method is used to segment the biopores in CT images of soil samples. Results are compared to indicator kriging, global thresholding, and extract holes. The variational method yields the smoothest and best connected system of large pores. Global thresholding is a competitive and objective alternative. … (more)
- Is Part Of:
- Computers & geosciences. Volume 98(2017)
- Journal:
- Computers & geosciences
- Issue:
- Volume 98(2017)
- Issue Display:
- Volume 98, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 98
- Issue:
- 2017
- Issue Sort Value:
- 2017-0098-2017-0000
- Page Start:
- 1
- Page End:
- 8
- Publication Date:
- 2017-01
- Subjects:
- 3D image segmentation -- Bio-pores -- Root system -- Variational segmentation -- Total variation minimization -- Gray value thresholding -- Morphological segmentation
Environmental policy -- Periodicals
550.5 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00983004 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cageo.2016.09.013 ↗
- Languages:
- English
- ISSNs:
- 0098-3004
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.695000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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