NEWS AND PRESS

The purpose of this study was to explore the effects of the integration of machine learning into daily radiological diagnostics, using the example of the machine learning software mdbrain® (Mediaire GmbH, Germany) in the diagnostic MRI workflow of patients with multiple sclerosis at the University Medicine Greifswald.

The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington’s disease using a certified software for automated volumetry and to compare the results with the manual measurement methods used in clinical practice as well as volume calculations of the caudate nuclei based on manual segmentations.

To evaluate the impact of an AI-based software trained to detect cerebral aneurysms on TOF-MRA on the diagnostic performance and reading times across readers with varying experience levels.

Published in Brain Communications, Volume 5, Issue 6, 2023 Authors Purrer, V., Pohl, E., Lueckel, J. M., Borger, V., Sauer, M., Radbruch, A., Wüllner, U., Schmeel, F. C. Abstract Essential tremor and Parkinson’s disease patients may present with various tremor types. Overlapping tremor features can be challenging to diagnosis and

Published in Life (2023), 13(1):16 Authors Bruno, F., Tommasino, E., Catalucci, A., Pastorelli, C., Borea, F., Caldarelli, G., Bellini, M., Badini, P., Mancini, S., Santobuono, C., et al. Abstract The purpose of the study is to quantify volumetric variations of cortical and subcortical brain structures after Vim ablation using MRgFUS, and

Published in Diagnostics (2023) Authors Bendella, Z., Widmann, C.N., Layer, J.P., Layer, Y.L., Haase, R., Sauer, M., Bieler, L., Lehnen, N.C., Paech, D., Heneka, M.T., Radbruch, A., Schmeel, F.C. Abstract Cohort studies that quantify volumetric brain data among individuals with different levels of COVID-19 severity are presently limited. It is

Published in American Journal of Neuroradiology (2022) Authors N.C. Lehnen, R. Haase, F.C. Schmeel, H. Vatter, F. Dorn, A. Radbruch and D. Paech Abstract Background and Purpose Cerebral aneurysms yield the risk of rupture, severe disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely treatment, if necessary. AI-based software tools are expected to

Presented at Clinical Neuroradiology, 31(Supplement 1), 40-41. (2021) Authors Aruci, M., Dünnwald, M., Schreiber, F., Sciarra, A., Maass, A., Schreiber, S., Oeltze-Jafra, S. Abstract Purpose White matter hyperintensities of presumed vascular origin (WMH), a hallmark feature of cerebral small vessel disease (CSVD), are FLAIR/T2-hyperintense lesions that predict various clinical readouts,

Published in Radiologie up2date 2022; 22 (2): 121–136 (2022) Authors M.-L. Kromrey, S. Grothe, C. Nell, B. Rosenberg Abstract Due to the enormous amount of digital data clinical radiology is highly suitable for the successful operation of artificial intelligence (AI). AI is a rather diffuse term, which describes the ability

Published in Frontiers in Neuroscience (2022) Authors Dalbis T., Fritz T., Grilo J., Hitziger S., Ling W. X. Abstract We present a deep learning method for the segmentation of new lesions in longitudinal FLAIR MRI sequences acquired at two different time points. In our approach, the 3D volumes are processed