{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T02:48:53Z","timestamp":1775702933891,"version":"3.50.1"},"reference-count":86,"publisher":"Walter de Gruyter GmbH","issue":"2","license":[{"start":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T00:00:00Z","timestamp":1501200000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,7,28]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Osteoarthritis is a degenerative disease affecting bones and cartilage especially in the human knee. In this context, cartilage thickness is an indicator for knee cartilage health. Thickness measurements are performed on medical images acquired<jats:italic>in-vivo<\/jats:italic>. Currently, there is no standard method agreed upon that defines a distance measure in articular cartilage. In this work, we present a comparison of different methods commonly used in literature. These methods are based on nearest neighbors, surface normal vectors, local thickness and potential field lines. All approaches were applied to manual segmentations of tibia and lateral and medial tibial cartilage performed by experienced raters. The underlying data were contrast agent-enhanced cone-beam C-arm CT reconstructions of one healthy subject\u2019s knee. The subject was scanned three times, once in supine position and two times in a standing weight-bearing position. A comparison of the resulting thickness maps shows similar distributions and high correlation coefficients between the approaches above 0.90. The nearest neighbor method results on average in the lowest cartilage thickness values, while the local thickness approach assigns the highest values. We showed that the different methods agree in their thickness distribution. The results will be used for a future evaluation of cartilage change under weight-bearing conditions.<\/jats:p>","DOI":"10.1515\/jib-2017-0015","type":"journal-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T10:07:53Z","timestamp":1501236473000},"source":"Crossref","is-referenced-by-count":12,"title":["Comparison of Different Approaches for Measuring Tibial Cartilage Thickness"],"prefix":"10.1515","volume":"14","author":[{"given":"Jennifer","family":"Maier","sequence":"first","affiliation":[{"name":"Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"}]},{"given":"Marianne","family":"Black","sequence":"additional","affiliation":[{"name":"Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, USA"}]},{"given":"Serena","family":"Bonaretti","sequence":"additional","affiliation":[{"name":"Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, USA"}]},{"given":"Bastian","family":"Bier","sequence":"additional","affiliation":[{"name":"Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"}]},{"given":"Bjoern","family":"Eskofier","sequence":"additional","affiliation":[{"name":"Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"}]},{"given":"Jang-Hwan","family":"Choi","sequence":"additional","affiliation":[{"name":"Division of Mechanical and Biomedical Engineering, Ewha Womans University, Seoul, Korea"}]},{"given":"Marc","family":"Levenston","sequence":"additional","affiliation":[{"name":"Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, USA"}]},{"given":"Garry","family":"Gold","sequence":"additional","affiliation":[{"name":"Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, USA"}]},{"given":"Rebecca","family":"Fahrig","sequence":"additional","affiliation":[{"name":"Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, USA"},{"name":"Now with Siemens Healthcare GmbH, Erlangen, Germany"}]},{"given":"Andreas","family":"Maier","sequence":"additional","affiliation":[{"name":"Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"}]}],"member":"374","reference":[{"key":"ref801","first-page":"58","volume-title":"Automatic motion estimation and compensation framework for weight-bearing C-arm CT scans using fiducial markers","year":"2015"},{"key":"ref821","doi-asserted-by":"crossref","first-page":"061902","DOI":"10.1118\/1.4873675","article-title":"Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. 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