Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

This paper addresses the significant problem of identifying the relevant background and
contextual literature related to deep learning (DL) as an evolving technology in order to …

Map‐like visualizations of patient‐specific cardiovascular structures have been applied in
numerous medical application contexts. The term map‐like alludes to the characteristics …

Recently, machine learning is massively on the rise in medical applications providing the
ability to predict diseases, plan treatment and monitor progress. Still, the use in a clinical …

Combining elements of biology, chemistry, physics, and medicine, the science of human
physiology is complex and multifaceted. In this report, we offer a broad and multiscale …

In many applications, visual analytics (VA) has developed into a standard tool to ease data
access and knowledge generation. VA describes a holistic cycle transforming data into …

Abstract​ Dieses Open-Access-essential schafft Orientierung, wenn Künstliche Intelligenz
im klinischen Alltag eingesetzt wird. Die Herausforderungen werden anhand zweier …

Analyzing stenoses of the internal carotids–local constrictions of the artery–is a critical
clinical task in cardiovascular disease treatment and prevention. For this purpose, we …

Visualizing neuroimaging data is a key step in evaluating data quality, interpreting results,
and communicating findings. This survey focuses on diffusion MRI tractography, which has …

We investigate uncertainty guidance mechanisms to support proton therapy (PT) planning
visualization. Uncertainties in the PT workflow pose significant challenges for navigating …