Improving bone strength prediction in human proximal femur specimens through geometrical characterization of trabecular bone microarchitecture and support vector regression

We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose,...

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Main Authors: Yang, Chien-Chun, Nagarajan, Mahesh B., Huber, Markus B., Carballido-Gamio, Julio, Bauer, Jan S., Baum, Thomas, Eckstein, Felix, Lochmüller, Eva, Majumdar, Sharmila, Link, Thomas M., Wismüller, Axel
Formato: Artigo
Idioma:Inglês
Publicado: 2014
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Article
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC4030629/
https://ncbi.nlm.nih.gov/pubmed/24860245
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JEI.23.1.013013
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