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Feature space clustering for trabecular bone segmentation
Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute of Technology, School of Technology and Health, Sweden.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0003-0884-899X
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute of Technology, School of Technology and Health, Sweden.ORCID iD: 0000-0002-7750-1917
KTH Royal Institute of Technology, School of Technology and Health, Sweden.
2017 (English)In: Image Analysis - 20th Scandinavian Conference on Image Analysis, SCIA 2017, Proceedings / [ed] Sharma P., Bianchi F., Springer, 2017, Vol. 10270, p. 65-70Conference paper, Published paper (Refereed)
Abstract [en]

Trabecular bone structure has been shown to impact bone strength and fracture risk. In vitro, this structure can be measured by micro-computed tomography (micro-CT). For clinical use, it would be valuable if multi-slice computed tomography (MSCT) could be used to analyse trabecular bone structure. One important step in the analysis is image volume segmentation. Previous segmentation techniques have either been computer resource intensive or produced suboptimal results when used on MSCT data. This paper proposes a new segmentation method that tries to balance good results against computational complexity.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 10270, p. 65-70
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10270
Keywords [en]
Clustering, Feature-space, Segmentation, Trabecular bone
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:liu:diva-142938DOI: 10.1007/978-3-319-59129-2_6ISBN: 978-3-319-59128-5 (print)ISBN: 978-3-319-59129-2 (electronic)OAI: oai:DiVA.org:liu-142938DiVA, id: diva2:1156459
Conference
20th Scandinavian Conference on Image Analysis (SCIA), Tromsö 12-14 juni 2017
Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2018-03-26

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Klintström, EvaSmedby, Örjan

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Center for Medical Image Science and Visualization (CMIV)Division of Radiological SciencesFaculty of Medicine and Health SciencesDepartment of Radiology in Linköping
Radiology, Nuclear Medicine and Medical Imaging

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