21 citations · 26 across the 4 of their papers we have counts for
4 papers
Current State of Community-Driven Radiological AI Deployment in Medical Imaging
Vikash Gupta, Barbaros Selnur Erdal, Carolina Ramirez +24
Artificial Intelligence (AI) has become commonplace to solve routine everyday tasks. Because of the exponential growth in medical imaging data volume and complexity, the workload o…
Quality monitoring of federated Covid-19 lesion segmentation
Camila Gonzalez, Christian Harder, Amin Ranem +5
Federated Learning is the most promising way to train robust Deep Learning models for the segmentation of Covid-19-related findings in chest CTs. By learning in a decentralized fas…
Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
Camila Gonzalez, Karol Gotkowski, Andreas Bucher +3
Automatic segmentation of lung lesions in computer tomography has the potential to ease the burden of clinicians during the Covid-19 pandemic. Yet predictive deep learning models a…
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…