%0 journal article %@ 1063-4584 %A Linka, K., Thüring, J., Rieppo, L., Aydin, R., Cyron, C., Kuhl, C., Merhof, D., Truhn, D., Nebelung, S. %D 2021 %J Osteoarthritis and Cartilage %N 4 %P 592-602 %R doi:10.1016/j.joca.2020.12.022 %T Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition %U https://doi.org/10.1016/j.joca.2020.12.022 4 %X Once trained for the clinical setting, advanced machine learning techniques, in particular ANNs, may be used to non-invasively determine compositional features of cartilage based on quantitative MRI parameters with potential implications for the diagnosis of (early) degeneration and for the monitoring of therapeutic outcomes.