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Estimation of Trabecular Thickness in Gray-Scale Images Through Granulometric Analysis
Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.ORCID iD: 0000-0001-5765-2964
Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9267-2191
Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0002-7750-1917
2012 (English)In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 2012Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

This paper extends to gray-scale the method proposed by Hildebrand and Ru ̈egsegger for estimating thickness of trabecular bone, which is the most used in trabecular bone research, where local thickness at a point is defined as the diameter of the maximum inscribed ball that includes that point. The proposed extension takes advantage of the equivalence between this method and the opening function computed for the granulometry generated by the opening operation of mathematical morphology with ball-shaped structuring elements of different radii. The proposed extension (a) uses gray-scale instead of binary mathematical morphology, (b) uses all values of the pattern spectrum of the granulometry instead of the maximum peak as used for binary images, (c) corrects bias on local thickness estimations generated by partial volume effects, and (d) uses the gray-scale as a weighting function for global thickness estimation. The proposed extension becomes equivalent to the original method when it is applied to binary images. A new non-flat structuring element is also proposed in order to reduce the discretization errors generated by traditional flat structuring elements. Translation invariance can be attained by up-sampling the images through interpolation by a factor of two. Results for synthetic and real images show that the quality of the measurements obtained through the original method strongly depend on the binarization process, whereas the measurements obtained through the proposed extension does not. Consequently, the proposed extension is more appropriate for images with limited resolution where binarization is not trivial. 

Place, publisher, year, edition, pages
2012.
Keyword [en]
Thickness estimation, trabecular bone, mathematical morphology, granulometry
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-78898DOI: 10.1117/12.906734ISI: 000304820000177ISBN: 9780819489630 (print)OAI: oai:DiVA.org:liu-78898DiVA: diva2:536693
Conference
SPIE Medical Imaging, 4–9 February 2012, San Diego, CA, USA
Available from: 2012-06-24 Created: 2012-06-24 Last updated: 2014-10-08

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Moreno, RodrigoBorga, MagnusSmedby, Örjan

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Center for Medical Image Science and Visualization, CMIVRadiologyFaculty of Health SciencesMedical InformaticsThe Institute of TechnologyDepartment of Radiology in Linköping
Medical Image Processing

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