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Feature space clustering for trabecular bone segmentation
Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. KTH Royal Institute of Technology, School of Technology and Health, Sweden.
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping.ORCID-id: 0000-0003-0884-899X
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, 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 (engelsk)Inngår i: Image Analysis - 20th Scandinavian Conference on Image Analysis, SCIA 2017, Proceedings / [ed] Sharma P., Bianchi F., Springer, 2017, Vol. 10270, s. 65-70Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Springer, 2017. Vol. 10270, s. 65-70
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10270
Emneord [en]
Clustering, Feature-space, Segmentation, Trabecular bone
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-142938DOI: 10.1007/978-3-319-59129-2_6ISI: 000454360300006ISBN: 978-3-319-59128-5 (tryckt)ISBN: 978-3-319-59129-2 (digital)OAI: oai:DiVA.org:liu-142938DiVA, id: diva2:1156459
Konferanse
20th Scandinavian Conference on Image Analysis (SCIA), Tromsö 12-14 juni 2017
Tilgjengelig fra: 2017-11-13 Laget: 2017-11-13 Sist oppdatert: 2020-07-08

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