Meeting Banner
Abstract #4869

Feature Reduction and Selection: a Study on their Importance in the Context of Radiomics

Annika Liebgott1,2, Janik Steyer-Ege2, Tobias Hepp1, Thomas Küstner1,2,3, Konstantin Nikolaou1, Bin Yang2, and Sergios Gatidis1

1Diagnostic and Interventional Radiology, University Hospital of Tuebingen, Tübingen, Germany, 2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 3School of Biomedical Engineering and Imaging Sciences, King's College London/St Thomas' Hospital, London, United Kingdom

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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here