Publications

Annika Reinke, Minu D Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A Emre Kavur, Tim Rädsch, Carole H Sudre, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Florian Buettner, M Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A Cimini, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Daniel A Hashimoto, Michael M Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L Martel, Erik Meijering, Bjoern Menze, Karel G M Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M Rafelski, Nasir Rajpoot, Mauricio Reyes, Michael A Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I Sánchez, Shravya Shetty, Ronald M Summers, Abdel A Taha, Aleksei Tiulpin, Sotirios A Tsaftaris, Ben Van Calster, Gaël Varoquaux, Ziv R Yaniv, Paul F Jäger, and Lena Maier-Hein. Understanding metric-related pitfalls in image analysis validation. Nat. Methods, (21)2:182--194, Springer Science and Business Media LLC, February 2024. [PUMA: Zno analysis image pitfalls validation]

Miriam Louise Carnot, Lorenz Heinemann, Jan Braker, Tobias Schreieder, Johannes Kiesel, Maik Fröbe, Martin Potthast, and Benno Stein. On Stance Detection in Image Retrieval for Argumentation. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2562–2571, Association for Computing Machinery, New York, NY, USA, 2023. [PUMA: Xack argumentation detection image retrieval stance] URL

Jules Scholler, Joel Jonsson, Tomás Jordá-Siquier, Ivana Gantar, Laura Batti, Bevan L Cheeseman, Stéphane Pagès, Ivo F Sbalzarini, and Christophe M Lamy. Efficient image analysis for large-scale next generation histopathology using pAPRica. bioRxiv, January 2023. [PUMA: Efficient Yaff analysis generation histopathology image large-scale {pAPRica}]

Maksim Kukushkin, Martin Bogdan, and Thomas Schmid. On optimizing morphological neural networks for hyperspectral image classification. In Wolfgang Osten (Eds.), Sixteenth International Conference on Machine Vision (ICMV 2023), (13072):1307202, SPIE, 2024. [PUMA: classification computer deep hyperspectral image learning mathematical morphological morphology networks neuronal nopdf remote sensing vision] URL

Qinghe Zeng, Christophe Klein, Stefano Caruso, Pascale Maille, Narmin Ghaffari Laleh, Daniele Sommacale, Alexis Laurent, Giuliana Amaddeo, David Gentien, Audrey Rapinat, Hélène Regnault, Cécile Charpy, Cong Trung Nguyen, Christophe Tournigand, Raffaele Brustia, Jean Michel Pawlotsky, Jakob Nikolas Kather, Maria Chiara Maiuri, Nicolas Loménie, and Julien Calderaro. Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology. J. Hepatol., (77)1:116--127, Elsevier BV, July 2022. [PUMA: topic_lifescience artificial deep gene image immune intelligence; learning; pathology; signatures; slide whole]

Alexander Kurz, Katja Hauser, Hendrik Alexander Mehrtens, Eva Krieghoff-Henning, Achim Hekler, Jakob Nikolas Kather, Stefan Fröhling, Christof von Kalle, and Titus Josef Brinker. Uncertainty estimation in medical image classification: Systematic review. JMIR Med. Inform., (10)8:e36427, August 2022. [PUMA: topic_lifescience calibration; classification; deep detection; estimation image imaging; learning; medical network out-of-distribution uncertainty]

Didem Cifci, Sebastian Foersch, and Jakob Nikolas Kather. Artificial intelligence to identify genetic alterations in conventional histopathology. J. Pathol., (257)4:430--444, Wiley, July 2022. [PUMA: topic_lifescience analysis; artificial biomarker; image intelligence; oncology precision]

Johannes Kiesel, Cagrı Cöltekin, Maximilian Heinrich, Maik Fröbe, Milad Alshomary, Bertrand De Longueville, Tomaz Erjavec, Nicolas Handke, Matyás Kopp, Nikola Ljubesić, Katja Meden, Nailia Mirzhakhmedova, Vaidas Morkevicius, Theresa Reitis-Münstermann, Mario Scharfbillig, Nicolas Stefanovitch, Henning Wachsmuth, Martin Potthast, and Benno Stein. Overview of Touché 2024: Argumentation Systems. Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024, Proceedings, Part V, 466–473, Springer-Verlag, Berlin, Heidelberg, 2024. [PUMA: topic_language Argumentation, Human Ideology, Image retrieval values,] URL

Akshay Akshay, Mitali Katoch, Masoud Abedi, Navid Shekarchizadeh, Mustafa Besic, Fiona C Burkhard, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, and Ali Hashemi Gheinani. SpheroScan: a user-friendly deep learning tool for spheroid image analysis. Gigascience, (12)Oxford University Press (OUP), December 2022. [PUMA: topic_federatedlearn 3D Image Mask R-CNN; analysis; deep high-throughput image learning; screening; segmentation spheroids;]