Rapid advances in image processing capabilities have been seen across many domains,
fostered by the application of machine learning algorithms to" big-data". However, within the …

Segmentation of MRI scans is a critical part of the workflow process before we can further
analyze neuroimaging data. Although there are several automatic tools for segmentation, no …

Deep-learning-based pipelines have shown the potential to revolutionalize microscopy
image diagnostics by providing visual augmentations and evaluations to a trained pathology …

Zusammenfassung Modern, state-of-the-art deep learning approaches yield human like
performance in numerous object detection and classification tasks. The foundation for their …

Web technology has transformed our lives, and has led to a paradigm shift in the
computational sciences. As the neuroimaging informatics research community amasses …

Modern, state-of-the-art deep learning approaches yield human like performance in
numerous object detection and classification tasks. The foundation for their success is the …

Deep learning methods are the de facto solutions to a multitude of medical image analysis
tasks. Cardiac MRI segmentation is one such application, which, like many others, requires …

In this work, we present a novel approach to generate large amounts of training data for
supervised machine learning algorithms. Traditionally, labeling a high quantity of data …