PD Dr. med. Sebastian Bickelhaupt

Institute of Radiology

Lesion-conditioning of synthetic MRI-derived subtraction-MIPs of the breast using a latent diffusion model (2024) Kapsner L, Folle L, Hadler D, Eberle J, Balbach E, Liebert A, Ganslandt T, et al. Journal article Lesion-mimicking DIXON swap artifact in contrast-enhanced subtraction breast MRI (2024) Bickelhaupt S, Laun FB, Uder M, Ohlmeyer S Journal article Effect of simultaneous multislice imaging, slice properties, and repetition time on the measured magnetic resonance biexponential intravoxel incoherent motion in the liver (2024) Loh M, Führes T, Stuprich C, Benkert T, Bickelhaupt S, Uder M, Laun FB Journal article Stability of Radiomic Features against Variations in Lesion Segmentations Computed on Apparent Diffusion Coefficient Maps of Breast Lesions (2024) Pistel M, Brock L, Laun FB, Erber R, Weiland E, Uder M, Wenkel E, et al. Journal article Diffusion-Weighted Imaging for Skin Pathologies of the Breast—A Feasibility Study (2024) Skwierawska D, Laun FB, Wenkel E, Kapsner L, Janka RM, Uder M, Ohlmeyer S, Bickelhaupt S Journal article Initial experience with a next-generation low-field MRI scanner: Potential for breast imaging? (2024) Dietzel M, Laun FB, Heiß R, Wenkel E, Bickelhaupt S, Hack C, Uder M, Ohlmeyer S Journal article Lungenbildgebung in der Niederfeld-Magnetresonanztomographie (2024) Hinsen M, Heiß R, Nagel AM, Levy S, Uder M, Bickelhaupt S, May M Journal article, Review article How to best match voxels - evaluating different sequential co-registration strategies for ultra-high b-value DWI in multiparametric breast MRI (2024) Brock L, Liebert A, Schreiter H, Ehring C, Eberle J, Laun FB, Uder M, et al. Conference contribution, Abstract of a poster Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs (2023) Führes T, Saake M, Szczepankiewicz F, Bickelhaupt S, Uder M, Laun FB Journal article Detection and prediction of background parenchymal enhancement on breast MRI using deep learning (2023) Das BK, Kapsner L, Ohlmeyer S, Laun FB, Maier A, Uder M, Wenkel E, et al. Conference contribution