1 citations · 1 across the 5 of their papers we have counts for
5 papers
Entropy Bootstrapping for Weakly Supervised Nuclei Detection
James Willoughby, Irina Voiculescu
Microscopy structure segmentation, such as detecting cells or nuclei, generally requires a human to draw a ground truth contour around each instance. Weakly supervised approaches (…
Salt & Pepper Heatmaps: Diffusion-informed Landmark Detection Strategy
Julian Wyatt, Irina Voiculescu
Anatomical Landmark Detection is the process of identifying key areas of an image for clinical measurements. Each landmark is a single ground truth point labelled by a clinician. A…
Runtime Freezing: Dynamic Class Loss for Multi-Organ 3D Segmentation
James Willoughby, Irina Voiculescu
Segmentation has become a crucial pre-processing step to many refined downstream tasks, and particularly so in the medical domain. Even with recent improvements in segmentation mod…
Triple-View Feature Learning for Medical Image Segmentation
Ziyang Wang, Irina Voiculescu
Deep learning models, e.g. supervised Encoder-Decoder style networks, exhibit promising performance in medical image segmentation, but come with a high labelling cost. We propose T…
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images
Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu
Using decentralized data for federated training is one promising emerging research direction for alleviating data scarcity in the medical domain. However, in contrast to large-scal…