Before revision: When artificial intelligence is used in the medical sector, interpretability is a crucial factor to consider. Diagnosis based on machine decision produced by a black-box neural network, sometimes lacking clear rationale, is unlikely to be clinically adopted for fear of potentially dire consequences arising from unexplained misdiagnosis. In this work, we implement Layer-wise Relevance Propagation (LRP) , a visual interpretability method applied on 3D U-Net for lesion segmentation using the small dataset of multi-modal images provided by ISLES 2017 competition.
After revision: We implement a visual interpretability method Layer-wise Relevance Propagation (LRP) , a visual interpretability method applied on 3D U-Net for lesion segmentation using the small dataset of multi-modal images provided by ISLES 2017 competition.