A Self-Normalization Reconstruction Technique for PET Scans Using the Positron Emission Data. - André Salomon; Benjamin Goldschmidt; René M. Botnar; Fabian Kiessling; Volkmar Schulz (IEEE Trans. Medical Imaging, 2012)

Spatio-Temporal Simulation of First Pass Drug Perfusion in the Liver. - Lars Ole Schwen; Markus Krauss; Christoph Niederalt; Felix Gremse; Fabian Kiessling; Andrea Schenk; Tobias Preusser; Lars Kuepfer (PLoS Comput. Biol., 2014)

GPU-Accelerated Sparse Matrix-Matrix Multiplication by Iterative Row Merging. - Felix Gremse; Andreas Höfter; Lars Ole Schwen; Fabian Kiessling; Uwe Naumann (SIAM J. Sci. Comput., 2015)

A Digital Preclinical PET/MRI Insert and Initial Results. - Bjoern Weissler; Pierre Gebhardt; Peter M. Dueppenbecker; Jakob Wehner; David Schug; Christoph W. Lerche; Benjamin Goldschmidt; André Salomon; Iris Verel; Edwin Heijman; Michael Perkuhn; Dirk Heberling; et al. (IEEE Trans. Medical Imaging, 2015)

GPU-accelerated adjoint algorithmic differentiation. - Felix Gremse; Andreas Höfter; Lukas Razik; Fabian Kiessling; Uwe Naumann (Comput. Phys. Commun., 2016)

Software-Based Real-Time Acquisition and Processing of PET Detector Raw Data. - Benjamin Goldschmidt; David Schug; Christoph W. Lerche; André Salomon; Pierre Gebhardt; Bjoern Weissler; Jakob Wehner; Peter M. Dueppenbecker; Fabian Kiessling; Volkmar Schulz (IEEE Trans. Biomed. Eng., 2016)

Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. - Tianyu Han; Sven Nebelung; Federico Pedersoli; Markus Zimmermann; Maximilian Schulze-Hagen; Michael Ho; Christoph Haarburger; Fabian Kiessling; Christiane Kuhl; Volkmar Schulz; Daniel Truhn (CoRR, 2020)

Hybrid MPI-MRI System for Dual-Modal In Situ Cardiovascular Assessments of Real-Time 3D Blood Flow Quantification - A Pre-Clinical In Vivo Feasibility Investigation. - Jochen Franke; Nicoleta Baxan; Heinrich Lehr; Ulrich Heinen; Sebastian Reinartz; Jörg Schnorr; Michael Heidenreich; Fabian Kiessling; Volkmar Schulz (IEEE Trans. Medical Imaging, 2020)

Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. - Tianyu Han; Jakob Nikolas Kather; Federico Pedersoli; Markus Zimmermann; Sebastian Keil; Maximilian Schulze-Hagen; Marc Terwoelbeck; Peter Isfort; Christoph Haarburger; Fabian Kiessling; Volkmar Schulz; Christiane Kuhl; et al. (CoRR, 2021)

An Anatomical Thermal 3D Model in Preclinical Research: Combining CT and Thermal Images. - Franziska Schollemann; Carina Barbosa Pereira; Stefanie Rosenhain; Andreas Follmann; Felix Gremse; Fabian Kiessling; Michael Czaplik; Mauren Abreu de Souza (Sensors, 2021)

Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. - Tianyu Han; Jakob Nikolas Kather; Federico Pedersoli; Markus Zimmermann; Sebastian Keil; Maximilian Schulze-Hagen; Marc Terwoelbeck; Peter Isfort; Christoph Haarburger; Fabian Kiessling; Christiane Kuhl; Volkmar Schulz; et al. (Nat. Mac. Intell., 2022)

A proof-of-concept pipeline to guide evaluation of tumor tissue perfusion by dynamic contrast-agent imaging: Direct simulation and inverse tracer-kinetic procedures. - Irene E. Vignon-Clementel; Nick Jagiella; Jules Dichamp; Jérôme Kowalski; Wiltrud Lederle; Hendrik Laue; Fabian Kiessling; Oliver Sedlaczek; Dirk Drasdo (Frontiers Bioinform., 2023)

Overcoming data scarcity in biomedical imaging with a foundational multi-task model. - Raphael Schäfer; Till Nicke; Henning Höfener; Annkristin Lange; Dorit Merhof; Friedrich Feuerhake; Volkmar Schulz; Johannes Lotz 002; Fabian Kiessling (Nat. Comput. Sci., 2024)

Tissue concepts: Supervised foundation models in computational pathology. - Till Nicke; Raphael Schäfer; Henning Höfener; Friedrich Feuerhake; Dorit Merhof; Fabian Kiessling; Johannes Lotz 002 (Comput. Biol. Medicine, 2025)

Evaluation of a Mouse-Sized Radial Gradiometer Receive Coil for Magnetic Particle Imaging. - Franziska Schrank; Harald Radermacher; Jochen Franke; Sébastien Breham; Fabian Kiessling; Volkmar Schulz (IEEE Trans. Instrum. Meas., 2025)