Automatic analysis of trabecular bone structure from knee MRI

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Joselene Marques, Rabia Granlund, Martin Lillholm, Paola C. Pettersen, Erik B. Dam

We investigated the feasibility of quantifying osteoarthritis (OA) by analysis of the trabecular bone
structure in low-¿eld knee MRI. Generic texture features were extracted from the images and
subsequently selected by sequential ¿oating forward selection (SFFS), following a fully automatic,
uncommitted machine-learning based framework. Six different classi¿ers were evaluated in crossvalidation schemes and the results showed that the presence of OA can be quanti¿ed by a bone
structure marker. The performance of the developed marker reached a generalization area-under-theROC (AUC) of 0.82, which is higher than the established cartilage markers known to relate to the OA diagnosis.
TidsskriftComputers in Biology and Medicine
Udgave nummer7
Sider (fra-til)735-742
Antal sider8
StatusUdgivet - 2012

ID: 40995413