|ECR 2015 / B-0244|
|Large-scale objective comparison of 29 novel algorithms for computer-aided diagnosis of dementia based on structural MRI|
|This poster is published under an open license. Please read the disclaimer for further details.|
While early and accurate diagnosis of dementia is challenging, computer-aided diagnosis methods based on quantitative biomarkers such as structural MRI can aid this (Klöppel et al., 2012). These methods use machine learning techniques that train a model to differentiate groups and make the diagnosis. Such algorithms for computer-aided diagnosis of dementia have shown very promising results for diagnosing Alzheimer’s disease (AD) and mild cognitive impairment (MCI) (Falahati et al., 2014). However, comparison of these algorithms is difficult as for evaluation often different data sets and methodology are used. In addition, it is not always clear how the performances of these algorithms would generalize to clinical data. Therefore, we performed a large-scale objective comparison study, CADDementia (Fig. 1), in which we compared algorithms for computer-aided diagnosis of dementia using structural MRI. Our aim was to evaluate how well these methods can reproduce clinical diagnoses, distinguishing patients with AD, MCI and controls (CN).
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