@inproceedings{d920d150ea054693a4fb06c67978a60a,
title = "Local binary patterns to evaluate trabecular bone structure from micro-CT data: Application to studies of human osteoarthritis",
abstract = "Osteoarthritis (OA) causes progressive degeneration of articular cartilage and pathological changes in subchondral bone. These changes can be assessed volumetrically using micro-computed tomography (μCT) imaging. The local descriptor, i.e. local binary pattern (LBP), is a new alternative solution to perform analysis of local bone structures from μCT scans. In this study, different trabecular bone samples were prepared from patients diagnosed with OA and treated with total knee arthroplasty. The LBP descriptor was applied to correlate the distribution of local patterns with the severity of the disease. The results obtained suggest the appearance and disappearance of specific oriented patterns with OA, as an adaptation of the bone to the decrease of cartilage thickness. The experimental results suggest that the LBP descriptor can be used to assess the changes in the trabecular bone due to OA.",
keywords = "Bone structural analysis, Micro-CT, Multiscale LBP, Osteoarthritis",
author = "J{\'e}r{\^o}me Thevenot and Jie Chen and Mikko Finnil{\"a} and Miika Nieminen and Petri Lehenkari and Simo Saarakkala and Matti Pietik{\"a}inen",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 13th European Conference on Computer Vision, ECCV 2014 ; Conference date: 06-09-2014 Through 12-09-2014",
year = "2015",
doi = "10.1007/978-3-319-16181-5\_5",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "63--79",
editor = "Carsten Rother and Bronstein, \{Michael M.\} and Lourdes Agapito",
booktitle = "Computer Vision - ECCV 2014 Workshops, Proceedings",
address = "Germany",
}