M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning
Abstract
M3d-CAM is an easy to use library for generating attention maps of CNN-based PyTorch models improving the interpretability of model predictions for humans. The attention maps can be generated with multiple methods like Guided Backpropagation, Grad-CAM, Guided Grad-CAM and Grad-CAM++. These attention maps visualize the regions in the input data that influenced the model prediction the most at a certain layer. Furthermore, M3d-CAM supports 2D and 3D data for the task of classification as well as for segmentation. A key feature is also that in most cases only a single line of code is required for generating attention maps for a model making M3d-CAM basically plug and play.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2020
- DOI:
- 10.48550/arXiv.2007.00453
- arXiv:
- arXiv:2007.00453
- Bibcode:
- 2020arXiv200700453G
- Keywords:
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- Computer Science - Computer Vision and Pattern Recognition;
- Computer Science - Machine Learning