SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks

20 Feb 2017Patrick Ferdinand ChristFlorian EttlingerGeorgios KaissisSebastian SchlechtFreba AhmaddyFelix GrünAlexander ValentinitschSeyed-Ahmad AhmadiRickmer BrarenBjoern Menze

Automatic non-invasive assessment of hepatocellular carcinoma (HCC) malignancy has the potential to substantially enhance tumor treatment strategies for HCC patients. In this work we present a novel framework to automatically characterize the malignancy of HCC lesions from DWI images... (read more)

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