11 citations · 35 across the 11 of their papers we have counts for
4 papers · 1 filter
End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging
Gerard Snaauw, Dong Gong, Gabriel Maicas +4
Cardiac magnetic resonance (CMR) is used extensively in the diagnosis and management of cardiovascular disease. Deep learning methods have proven to deliver segmentation results co…
Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI
Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento +2
We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., labels are available only at the im…
Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI
Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley +2
There is a heated debate on how to interpret the decisions provided by deep learning models (DLM), where the main approaches rely on the visualization of salient regions to interpr…
Training Medical Image Analysis Systems like Radiologists
Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento +2
The training of medical image analysis systems using machine learning approaches follows a common script: collect and annotate a large dataset, train the classifier on the training…