Can Masses of Non-Experts Train Highly Accurate Image Classifiers? - A Crowdsourcing Approach to Instrument Segmentation in Laparoscopic Images. - Lena Maier-Hein; Sven Mersmann; Daniel Kondermann; Sebastian Bodenstedt; Alexandro Sanchez; Christian Stock; Hannes Götz Kenngott; Matthias Eisenmann; Stefanie Speidel (MICCAI (2), 2014)

Abstract: Können wir Rankings vertrauen? Eine systematische Analyse biomedizinischer Challenges hinsichtlich Reporting und Design. - Matthias Eisenmann; Patrick Scholz 001; Marko Stankovic 002; Pierre Jannin; Christian Stock; Lena Maier-Hein (Bildverarbeitung für die Medizin, 2017)

Surgical Data Science: Enabling Next-Generation Surgery. - Lena Maier-Hein; S. Swaroop Vedula; Stefanie Speidel; Nassir Navab; Ron Kikinis; Adrian Park 001; Matthias Eisenmann; Hubertus Feussner; Germain Forestier; Stamatia Giannarou; Makoto Hashizume; Darko Katic; et al. (CoRR, 2017)

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)

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)

Surgical Data Science: A Consensus Perspective. - Lena Maier-Hein; Matthias Eisenmann; Carolin Feldmann; Hubertus Feussner; Germain Forestier; Stamatia Giannarou; Bernard Gibaud; Gregory D. Hager; Makoto Hashizume; Darko Katic; Hannes Kenngott; Ron Kikinis; et al. (CoRR, 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; Peter M. Full (Zenodo, 2018)

Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room. - Lena Maier-Hein; Martin Wagner 001; Tobias Roß; Annika Reinke; Sebastian Bodenstedt; Peter M. Full; Hellena Hempe; Diana Mîndroc-Filimon; Patrick Scholz 001; Thuy Nuong Tran; Pierangela Bruno; Anna Kisilenko; et al. (CoRR, 2020)

Surgical Data Science - from Concepts to Clinical Translation. - Lena Maier-Hein; Matthias Eisenmann; Duygu Sarikaya; Keno März; Toby Collins; Anand Malpani; Johannes Fallert; Hubertus Feussner; Stamatia Giannarou; Pietro Mascagni; Hirenkumar Nakawala; Adrian Park 001; 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)

Abstract: How to Generate Patient Benefit with Surgical Data Science - Results of an International Delphi Process. - Matthias Eisenmann; Minu Dietlinde Tizabi; Keno März; Lena Maier-Hein (Bildverarbeitung für die Medizin, 2022)

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)

Biomedical image analysis competitions: The state of current participation practice. - Matthias Eisenmann; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Fabian Isensee; Tim J. Adler; Patrick Godau; Veronika Cheplygina; Michal Kozubek 001; Sharib Ali; Anubha Gupta; Jan Kybic; et al. (CoRR, 2022)

Surgical data science - from concepts toward clinical translation. - Lena Maier-Hein; Matthias Eisenmann; Duygu Sarikaya; Keno März; Toby Collins; Anand Malpani; Johannes Fallert; Hubertus Feussner; Stamatia Giannarou; Pietro Mascagni; Hirenkumar Nakawala; Adrian Park 001; et al. (Medical Image Anal., 2022)

A Delphi consensus statement for digital surgery. - Kyle Lam; Michael D. Abràmoff; José M. Balibrea; Steven M. Bishop; Richard R. Brady; Rachael Callcut; Manish Chand; Justin Collins; Markus K. Diener; Matthias Eisenmann; Kelly Fermont; Manoel Galvao Neto; et al. (npj Digit. Medicine, 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)

Application of the Metaverse in Product Engineering - A Workshop for Identification of Potential Field of Action. - Tobias Düser; Maximilian Fischer; Stefan Eric Schwarz; Annika Bastian; Jonas Freyer; Kristian Vlajic; Matthias Eisenmann; Sven Matthiesen; Albert Albers (METAVERSE, 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)

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. (CoRR, 2023)