Author

Hannes Schreiter

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Open access Nov 2026

Influence of dominant sequence artifacts on generative AI for virtual contrast-enhancement in breast MRI

Virtual contrast-enhanced (vCE) breast MRI is a deep learning approach for generating contrast-like images from non-contrast acquisitions. As diffusion-weighted imaging (DWI) has emerged as a major contributor to enhancement synthesis, understanding the influence of DWI-related image artifacts is important for the robu...

Luise Brock, Ameya Markale, Tri-Thien Nguyen et al. · BMC Medical Imaging · 0 citations

Open access Oct 2026

Influence of virtual dynamic contrast enhanced breast MRI on lesion size, BI-RADS scores and reader confidence.

BACKGROUND Breast MRI routinely uses gadolinium-based contrast agents (GBCAs) for dynamic contrast-enhanced (DCE) imaging. However, GBCA administration entails periprocedural effort and environmental impact, prompting exploration of contrast-agent-free approaches. Deep learning-based virtual DCE (vDCE) offers a potenti...

A. Liebert, Hannes Schreiter, L. Kapsner et al. · European Radiology · 0 citations

#diffusion models Open access Oct 2026

Slice-Wise Quality Assessment of High b Value Breast DWI via Deep Learning-Based Artifact Detection.

BACKGROUND Diffusion-weighted imaging (DWI) can support lesion detection and characterization in breast MRI. Therefore, DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. However, especially high b value DWI can be prone to intensity arti...

Ameya Markale, Luise Brock, Ihor Horishnyi et al. · Journal of Magnetic Resonanc... · 2 citations