Robust biclustering by sparse singular value decomposition incorporating stability selection. - Martin Sill; Sebastian Kaiser; Axel Benner; Annette Kopp-Schneider (Bioinform., 2011)

On the identification of predictive biomarkers: Detecting treatment-by-gene interaction in high-dimensional data. - Wiebke Werft; Axel Benner; Annette Kopp-Schneider (Comput. Stat. Data Anal., 2012)

How to Exploit Weaknesses in Biomedical Challenge Design and Organization. - Annika Reinke; Matthias Eisenmann; Sinan Onogur; Marko Stankovic 002; Patrick Scholz 001; Peter M. Full; Hrvoje Bogunovic; Bennett A. Landman; Oskar Maier; Bjoern H. Menze; Gregory C. Sharp; Korsuk Sirinukunwattana; et al. (MICCAI (4), 2018)

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning. - Tobias Roß; David Zimmerer; Anant Suraj Vemuri; Fabian Isensee; Manuel Wiesenfarth; Sebastian Bodenstedt; Fabian Both; Philip Kessler; Martin Wagner 001; Beat Müller; Hannes Kenngott; Stefanie Speidel; et al. (Int. J. Comput. Assist. Radiol. Surg., 2018)

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions. - Lena Maier-Hein; Matthias Eisenmann; Annika Reinke; Sinan Onogur; Marko Stankovic 002; Patrick Scholz 001; Tal Arbel; Hrvoje Bogunovic; Andrew P. Bradley; Aaron Carass; Carolin Feldmann; Alejandro F. Frangi; et al. (CoRR, 2018)

Optimal experimental designs for estimating the drug combination index in toxicology. - T. Holland-Letz; Annette Kopp-Schneider (Comput. Stat. Data Anal., 2018)

A large annotated medical image dataset for the development and evaluation of segmentation algorithms. - Amber L. Simpson; Michela Antonelli; Spyridon Bakas; Michel Bilello; Keyvan Farahani; Bram van Ginneken; Annette Kopp-Schneider; Bennett A. Landman; Geert Litjens 001; Bjoern H. Menze; Olaf Ronneberger; Ronald M. Summers; et al. (CoRR, 2019)

Methods and open-source toolkit for analyzing and visualizing challenge results. - Manuel Wiesenfarth; Annika Reinke; Bennett A. Landman; Manuel Jorge Cardoso; Lena Maier-Hein; Annette Kopp-Schneider (CoRR, 2019)

Robust Medical Instrument Segmentation Challenge 2019. - Tobias Roß; Annika Reinke; Peter M. Full; Martin Wagner 001; Hannes Kenngott; Martin Apitz; Hellena Hempe; Diana Mîndroc-Filimon; Patrick Scholz 001; Thuy Nuong Tran; Pierangela Bruno; Pablo Arbeláez; et al. (CoRR, 2020)

BIAS: Transparent reporting of biomedical image analysis challenges. - Lena Maier-Hein; Annika Reinke; Michal Kozubek 001; Anne L. Martel; Tal Arbel; Matthias Eisenmann; Allan Hanbury; Pierre Jannin; Henning Müller; Sinan Onogur; Julio Saez-Rodriguez; Bram van Ginneken; et al. (Medical Image Anal., 2020)

Common Limitations of Image Processing Metrics: A Picture Story. - Annika Reinke; Matthias Eisenmann; Minu Dietlinde Tizabi; Carole H. Sudre; Tim Rädsch; Michela Antonelli; Tal Arbel; Spyridon Bakas; M. Jorge Cardoso; Veronika Cheplygina; Keyvan Farahani; Ben Glocker; et al. (CoRR, 2021)

The Medical Segmentation Decathlon. - Michela Antonelli; Annika Reinke; Spyridon Bakas; Keyvan Farahani; Annette Kopp-Schneider; Bennett A. Landman; Geert Litjens 001; Bjoern H. Menze; Olaf Ronneberger; Ronald M. Summers; Bram van Ginneken; Michel Bilello; et al. (CoRR, 2021)

Machine learning-based analysis of hyperspectral images for automated sepsis diagnosis. - Maximilian Dietrich; Silvia Seidlitz; Nicholas Schreck; Manuel Wiesenfarth; Patrick Godau; Minu Tizabi; Jan Sellner; Sebastian Marx; Samuel Knödler; Michael M. Allers; Leonardo Ayala; Karsten Schmidt 007; et al. (CoRR, 2021)

How can we learn (more) from challenges? A statistical approach to driving future algorithm development. - Tobias Roß; Pierangela Bruno; Annika Reinke; Manuel Wiesenfarth; Lisa Koeppel; Peter M. Full; Bünyamin Pekdemir; Patrick Godau; Darya Trofimova; Fabian Isensee; Sara Moccia; Francesco Calimeri; et al. (CoRR, 2021)

Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge. - Tobias Roß; Annika Reinke; Peter M. Full; Martin Wagner 001; Hannes Kenngott; Martin Apitz; Hellena Hempe; Diana Mîndroc-Filimon; Patrick Scholz 001; Thuy Nuong Tran; Pierangela Bruno; Pablo Arbeláez; et al. (Medical Image Anal., 2021)

Metrics reloaded: Pitfalls and recommendations for image analysis validation. - Lena Maier-Hein; Annika Reinke; Evangelia Christodoulou; Ben Glocker; Patrick Godau; Fabian Isensee; Jens Kleesiek; Michal Kozubek 001; Mauricio Reyes 001; Michael A. Riegler; Manuel Wiesenfarth; Michael Baumgartner 001; et al. (CoRR, 2022)

Labeling instructions matter in biomedical image analysis. - Tim Rädsch; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Nicholas Schreck; A. Emre Kavur; Bünyamin Pekdemir; Tobias Roß; Annette Kopp-Schneider; Lena Maier-Hein (CoRR, 2022)

Why is the Winner the Best? - Matthias Eisenmann; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Fabian Isensee; Tim J. Adler; Sharib Ali; Vincent Andrearczyk; Marc Aubreville; Ujjwal Baid; Spyridon Bakas; Niranjan Balu; et al. (CVPR, 2023)

Understanding metric-related pitfalls in image analysis validation. - Annika Reinke; Minu Tizabi; Michael Baumgartner 001; Matthias Eisenmann; Doreen Heckmann-Nötzel; A. Emre Kavur; Tim Rädsch; Carole H. Sudre; Laura Ación; Michela Antonelli; Tal Arbel; Spyridon Bakas; et al. (CoRR, 2023)

Spectral imaging enables contrast agent-free real-time ischemia monitoring in laparoscopic surgery. - Leonardo Ayala; Tim Adler; Silvia Seidlitz; Sebastian J. Wirkert; Alexander Seitel; Jan Sellner; Anant Vemuri; Manuel Wiesenfarth; Nicholas Schreck; Sebastian Pirmann; Annette Kopp-Schneider; Lena Maier-Hein (Zenodo, 2023)

Labelling instructions matter in biomedical image analysis. - Tim Rädsch; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Nicholas Schreck; A. Emre Kavur; Bünyamin Pekdemir; Tobias Roß; Annette Kopp-Schneider; Lena Maier-Hein (Nat. Mac. Intell., 2023)

Beyond rankings: Learning (more) from algorithm validation. - Tobias Roß; Pierangela Bruno; Annika Reinke; Manuel Wiesenfarth; Lisa Koeppel; Peter M. Full; Bünyamin Pekdemir; Patrick Godau; Darya Trofimova; Fabian Isensee; Tim J. Adler; Thuy Nuong Tran; et al. (Medical Image Anal., 2023)

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark. - Martin Wagner 001; Beat P. Müller-Stich; Anna Kisilenko; Duc Tran; Patrick Heger; Lars Mündermann; David M. Lubotsky; Benjamin Müller; Tornike Davitashvili; Manuela Capek; Annika Reinke; Carissa Reid; et al. (Medical Image Anal., 2023)

Quality Assured: Rethinking Annotation Strategies in Imaging AI. - Tim Rädsch; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Nicholas Heller; Fabian Isensee; Annette Kopp-Schneider; Lena Maier-Hein (ECCV (78), 2024)

Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI? - Evangelia Christodoulou; Annika Reinke; Rola Houhou; Piotr Kalinowski; Selen Erkan; Carole H. Sudre; Ninon Burgos; Sofiène Boutaj; Sophie Loizillon; Maëlys Solal; Nicola Rieke; Veronika Cheplygina; et al. (MICCAI (10), 2024)

Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis. - Jan Sellner; Alexander Studier-Fischer; Ahmad Bin Qasim; Silvia Seidlitz; Nicholas Schreck; Minu Tizabi; Manuel Wiesenfarth; Annette Kopp-Schneider; Samuel Knödler; Caelan Max Haney; Gabriel Salg; Berkin Özdemir; et al. (CoRR, 2024)

False Promises in Medical Imaging AI? Assessing Validity of Outperformance Claims. - Evangelia Christodoulou; Annika Reinke; Pascaline Andrè; Patrick Godau; Piotr Kalinowski; Rola Houhou; Selen Erkan; Carole H. Sudre; Ninon Burgos; Sofiène Boutaj; Sophie Loizillon; Maëlys Solal; et al. (CoRR, 2025)