51 citations · 58 across the 10 of their papers we have counts for
4 papers · 1 filter
VIDS-Seg: Towards Reliable Uncertainty Quantification in Pediatric Cardiac Ultrasound Segmentation
Paul Fischer, Ece Ozkan
Reliable clinical deployment of machine learning requires models that know when they are likely to fail, particularly for subgroups underrepresented in training data. A common case…
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods
Ričards Marcinkevičs, Ece Ozkan, Julia E. Vogt
Deep neural networks for image-based screening and computer-aided diagnosis have achieved expert-level performance on various medical imaging modalities, including chest radiograph…
Siamese Networks with Location Prior for Landmark Tracking in Liver Ultrasound Sequences
Alvaro Gomariz, Weiye Li, Ece Ozkan +2
Image-guided radiation therapy can benefit from accurate motion tracking by ultrasound imaging, in order to minimize treatment margins and radiate moving anatomical targets, e.g.,…
Herding Generalizes Diverse M -Best Solutions
Ece Ozkan, Gemma Roig, Orcun Goksel +1
We show that the algorithm to extract diverse M -solutions from a Conditional Random Field (called divMbest [1]) takes exactly the form of a Herding procedure [2], i.e. a determini…