Background: An eye-related diabetic microvascular condition is called diabetic retinopathy
(DR). Injury to the retinal blood vessels, one of the main causes of blindness worldwide, is a …

Purpose Recently, brain tumor segmentation has made important progress. However, the
quality of manual labels plays an important role in the performance, while in practice, it could …

Deep convolutional neural networks for image segmentation do not learn the label structure
explicitly and may produce segmentations with an incorrect structure, eg, with disconnected …

Supervised deep learning methods offer the potential for automating lesion segmentation in
routine clinical brain imaging, but performance is dependent on label quality. In practice …

Deep-learning-based approaches for retinal lesion segmentation often require an abundant
amount of precise pixel-wise annotated data. However, coarse annotations such as circles …

Deep learning algorithms for image segmentation typically require large data sets with high-
quality annotations to be trained with. For many domains, the annotation cost for obtaining …

We aim to perform medical note comprehension and medical image processing, with an
ultimate goal of cross-domain aggregation into a cooperative disease management system …