Rickmer Braren

Rickmer Braren

Deputy Director Institute for Diagnostic and Interventional Radiology

Technical University of Munich

Publications

2026

Contrastive virtual staining enhances deep learning-based PDAC subtyping from H&E-stained tissue cores Maximilian Fischer, Alexander Muckenhuber, Robin Peretzke, Luay Farah, Constantin Ulrich, Sebastian Ziegler, Philipp Schader, Lorenz Feineis, Hanno Gao, Shuhan Xiao, Michael Götz, Marco Nolden, Katja Steiger, Jens T. Siveke, Lukas Endrös, Rickmer Braren, Jens Kleesiek, Peter Schüffler, Peter Neher, Klaus Maier-Hein The Journal of Pathology

2025

International Retrospective Observational Study of Continual Learning for AI on Endotracheal Tube Placement from Chest Radiographs Emma Chen, Agustina Saenz, Oishi Banerjee, Henrik Marklund, Xiaoman Zhang, Shreya Johri, Hong-Yu Zhou, Luyang Luo, Subathra Adithan, Kay Wu, Siddhant Dogra, Vijay Janapa Reddi, Dominic Buensalido, Helen Kavnoudias, Roman Kloeckner, Lukas Müller, Emmanuel Salinas-Miranda, Maria José Veloza Vega, Johannes Kolck, Tobias Penzkofer, Daiju Ueda, Shannon L. Walston, Armin Alvaro Quispe-Cornejo, Michele Salvagno, Christopher Lee, Jonathan Fournier, Rosa Patricia Castillo, Cibele Luna, Tara Bahramipour, Amanda Zuback, Rickmer Braren, Petra Jiraskova, Yutthaphan Wannasopha, Piyapong Khumrin, Desmond Lim Shi Wei Wei, James Thomas Patrick Decourcy Hallinan, Zhicheng Jiao, Thomas Yi, Juana Maria Plasencia Martinez, Nuria Isabel Casado Alarcon, Franz A. Fellner, Julian F. Niedermair, Derek Wu, Dongkeun Kim, Johannes Haubold, Lars Heiliger, Daniel Pérez-Chada, Pablo Pratesi, Ryan Cummings, Narges Razavian, Anastasia Oikonomou, William T. Tran, Thomas Küstner, Saif Afat, Adrienne N. Dula, Justin F. Rousseau, Franko Hržić, Michael Fuchsjäger, Pranav Rajpurkar NEJM AI Unlocking the potential of digital pathology: Novel baselines for compression Maximilian Fischer, Peter Neher, Peter Schüffler, Sebastian Ziegler, Shuhan Xiao, Robin Peretzke, David Clunie, Constantin Ulrich, Michael Baumgartner, Alexander Muckenhuber, Silvia Dias Almeida, Michael Götz, Jens Kleesiek, Marco Nolden, Rickmer Braren, Klaus Maier-Hein Journal of Pathology Informatics Learned Image Compression for HE-Stained Histopathological Images via Stain Deconvolution Maximilian Fischer, Peter Neher, Tassilo Wald, Silvia Dias Almeida, Shuhan Xiao, Peter Schüffler, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Jens Kleesiek, Marco Nolden, Klaus Maier-Hein Medical Optical Imaging and Virtual Microscopy Image Analysis

2024

Real-world federated learning in radiology: hurdles to overcome and benefits to gain Markus Ralf Bujotzek, Ünal Akünal, Stefan Denner, Peter Neher, Maximilian Zenk, Eric Frodl, Astha Jaiswal, Moon-Sung Kim, Nicolai R Krekiehn, Manuel Nickel, Richard Ruppel, Marcus Both, Felix Döllinger, Marcel Klaus Opitz, Thorsten Persigehl, Jens Kleesiek, Tobias Penzkofer, Klaus Maier-Hein, Andreas Bucher, Rickmer Braren Journal of the American Medical Informatics Association Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning Maximilian Fischer, Peter Neher, Peter Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus Maier-Hein Machine Learning in Medical Imaging Prognostic value of deep learning-derived body composition in advanced pancreatic cancer—a retrospective multicenter study Julius Keyl, Andreas Bucher, F. Jungmann, René Hosch, A. Ziller, R. Armbruster, P. Malkomes, T. M. Reissig, Sven Koitka, I. Tzianopoulos, Philipp Keyl, K. Kostbade, David Albers, Peter Markus, Jürgen Treckmann, Kai Nassenstein, Johannes Haubold, Marcus R. Makowski, Michael Forsting, Hideo A. Baba, Stefan Kasper, Jens T. Siveke, Felix Nensa, Martin Schuler, Georgios Kaissis, Jens Kleesiek, Rickmer Braren ESMO Open

2023

Current State of Community-Driven Radiological AI Deployment in Medical Imaging (Preprint) Vikash Gupta, Barbaros Selnur Erdal, Carolina Ramirez, Ralf Floca, Brad Genereaux, Sidney Bryson, Christopher P. Bridge, Jens Kleesiek, Felix Nensa, Rickmer Braren, Khaled Younis, Tobias Penzkofer, Andreas Bucher, Ming Melvin Qin, Gigon Bae, Hyeonhoon Lee, Jorge M Cardoso, Sebastien Ourselin, Eric Kerfoot, Rahul Choudhury, Richard D. White, Tessa Cook, David Bericat, Matthew Lungren, Risto Haukioja, Haris Shuaib JMIR AI

2022

Current State of Community-Driven Radiological AI Deployment in Medical Imaging Vikash Gupta, Barbaros Selnur Erdal, Carolina Ramirez, Ralf Floca, Laurence Jackson, Brad Genereaux, Sidney Bryson, Christopher P. Bridge, Jens Kleesiek, Felix Nensa, Rickmer Braren, Khaled Younis, Tobias Penzkofer, Andreas Bucher, Ming Melvin Qin, Gigon Bae, M. Jorge Cardoso, Sebastien Ourselin, Eric Kerfoot, Rahul Choudhury, Richard D. White, Tessa Cook, David Bericat, Matthew Lungren, Risto Haukioja, Haris Shuaib arXiv DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform Maximilian Fischer, Philipp Schader, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Wilko Weichert, Peter Schüffler, Jens Kleesiek, Jonas Scherer, Klaus Kades, Klaus Maier-Hein, Marco Nolden Bildverarbeitung für die Medizin 2022

2020

Joint Imaging Platform for Federated Clinical Data Analytics Jonas Scherer, Marco Nolden, Jens Kleesiek, Jasmin Metzger, Klaus Kades, Verena Schneider, Michael Bach, Oliver Lukas Sedlaczek, Andreas Bucher, Thomas J. Vogl, Frank Grünwald, Jens-Peter Kühn, Ralf-Thorsten Hoffmann, Jörg Kotzerke, Oliver Bethge, Lars Schimmöller, Gerald Antoch, Hans-Wilhelm Müller, Andreas Daul, Konstantin Nikolaou, Christian la Fougère, Wolfgang G. Kunz, Michael Ingrisch, Balthasar Schachtner, Jens Ricke, Peter Bartenstein, Felix Nensa, Alexander Radbruch, Lale Umutlu, Michael Forsting, Robert Seifert, Ken Herrmann, Philipp Mayer, Hans-Ulrich Kauczor, Tobias Penzkofer, Bernd Hamm, Winfried Brenner, Roman Kloeckner, Christoph Düber, Mathias Schreckenberger, Rickmer Braren, Georgios Kaissis, Marcus R. Makowski, Matthias Eiber, Andrei Gafita, Rupert Trager, Wolfgang A. Weber, Jakob Neubauer, Marco Reisert, Michael Bock, Fabian Bamberg, Jürgen Hennig, Philipp Tobias Meyer, Juri Ruf, Uwe Haberkorn, Stefan O. Schoenberg, Tristan Kuder, Peter Neher, Ralf Floca, Heinz-Peter Schlemmer, Klaus Maier-Hein JCO Clinical Cancer Informatics Wie funktioniert maschinelles Lernen? Jens Kleesiek, Jacob M. Murray, Christian Strack, Georgios Kaissis, Rickmer Braren Der Radiologe Wie funktioniert Radiomics? Jacob M. Murray, Georgios Kaissis, Rickmer Braren, Jens Kleesiek Der Radiologe

2019

Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung Jens Kleesiek, Jacob M. Murray, Georgios Kaissis, Rickmer Braren Der Onkologe