Direct Glyph-based Visualization of Diffusion MR Data Using Deformed Spheres. - Martin Domin; Sönke Langner; Norbert Hosten; Lars Linsen (Visualization in Medicine and Life Sciences, 2008)

Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. - Matthias Wilms; Jordan J. Bannister; Pauline Mouches; M. Ethan MacDonald; Deepthi Rajashekar; Sönke Langner; Nils D. Forkert (MLCN/RNO-AI@MICCAI, 2020)

Towards Self-explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows. - Matthias Wilms; Pauline Mouches; Jordan J. Bannister; Deepthi Rajashekar; Sönke Langner; Nils D. Forkert (MLCN@MICCAI, 2021)

Unifying Brain Age Prediction and Age-Conditioned Template Generation with a Deterministic Autoencoder. - Pauline Mouches; Matthias Wilms; Deepthi Rajashekar; Sönke Langner; Nils Daniel Forkert (MIDL, 2021)

CFD validation using in-vitro MRI velocity data - Methods for data matching and CFD error quantification. - Carolin Wüstenhagen; Kristine John; Sönke Langner; Martin Brede; Sven Grundmann; Martin Bruschewski (Comput. Biol. Medicine, 2021)

Disentangling Factors of Morphological Variation in an Invertible Brain Aging Model. - Matthias Wilms; Pauline Mouches; Jordan J. Bannister; Sönke Langner; Nils D. Forkert (MAD@MICCAI, 2022)

An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction. - Raissa Souza; Pauline Mouches; Matthias Wilms; Anup Tuladhar; Sönke Langner; Nils D. Forkert (J. Am. Medical Informatics Assoc., 2022)

Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging. - Matthias Wilms; Jordan J. Bannister; Pauline Mouches; M. Ethan MacDonald; Deepthi Rajashekar; Sönke Langner; Nils D. Forkert (IEEE Trans. Medical Imaging, 2022)