Enhancing the Extraction of Interpretable Information for Ischemic Stroke Imaging from Deep Neural Networks

19 Nov 2019Erico TjoaGuo HengLu YuhaoCuntai Guan

We implement a visual interpretability method Layer-wise Relevance Propagation (LRP) on top of 3D U-Net trained to perform lesion segmentation on the small dataset of multi-modal images provided by ISLES 2017 competition. We demonstrate that LRP modifications could provide more sensible visual explanations to an otherwise highly noise-skewed saliency map... (read more)

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