38 citations · 81 across the 13 of their papers we have counts for
4 papers · 1 filter
Continual Learning in Medical Imaging: A Survey and Practical Analysis
Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev +4
Deep Learning has shown great success in reshaping medical imaging, yet it faces numerous challenges hindering widespread application. Issues like catastrophic forgetting and distr…
Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts
Camila Gonzalez, Amin Ranem, Ahmed Othman +1
Most continual learning methods are validated in settings where task boundaries are clearly defined and task identity information is available during training and testing. We explo…
What is Wrong with Continual Learning in Medical Image Segmentation?
Camila Gonzalez, Nick Lemke, Georgios Sakas +1
Continual learning protocols are attracting increasing attention from the medical imaging community. In continual environments, datasets acquired under different conditions arrive…
M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning
Karol Gotkowski, Camila Gonzalez, Andreas Bucher +1
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 b…