Using large amounts of image features in the context of Radiomics to perform complex image analysis tasks yields promising results for clinical applications. While it is easy to extract a large amount of features from medical images, it is complex to select the right features for a specific scientific problem. This study aims to show, how important it is to pay attention to choosing the right technique to select the most suitable features by means of feature reduction or selection on the example of two Radiomics-related MR image classification tasks.
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