An integrative analysis of image segmentation and survival of brain tumour patients

Our contribution to the BraTS 2019 challenge consisted of a deep learning based approach for segmentation of brain tumours from MR images using cross validation ensembles of 2D-UNet models. Furthermore, different approaches for the prediction of patient survival time using clinical as well as imaging features were investigated.
A simple linear regression model using patient age and tumour volumes outperformed more elaborate approaches like convolutional neural networks or Radiomic-based analysis with an accuracy of 0.55 on the validation set.