Michael Alexander Riegler

Scientific publications

Vo, Minh-Quan; Nguyen, Thu; Riegler, Michael ; Hammer, Hugo Lewi (2024). Efficient Estimation of Generative Models Using Tukey Depth. Algorithms. Vol. 17.
https://doi.org/10.3390/a17030120

Chatterjee, Ayan; Gerdes, Martin; Prinz, Andreas; Riegler, Michael ; Martinez, Santiago (2024). Semantic representation and comparative analysis of physical activity sensor observations using MOX2-5 sensor in real and synthetic datasets: a proof-of-concept-study. Scientific Reports. Vol. 14.
https://doi.org/10.1038/s41598-024-55183-6

Maier-Hein, Lena; Reinke, Annika; Godau, Patrick; Tizabi, Minu D.; Buettner, Florian; Christodoulou, Evangelia; Glocker, Ben; Isensee, Fabian; Kleesiek, Jens; Kozubek, Michal; Reyes, Mauricio; Riegler, Michael ; Wiesenfarth, Manuel; Kavur, A. Emre; Sudre, Carole H.; Baumgartner, Michael; Eisenmann, Matthias; Heckmann-Nötzel, Doreen; Rädsch, Tim; Acion, Laura; Antonelli, Michela; Arbel, Tal; Bakas, Spyridon; Benis, Arriel; Blaschko, Matthew B.; Cardoso, M. Jorge; Cheplygina, Veronika; Cimini, Beth A.; Collins, Gary S.; Farahani, Keyvan; Ferrer, Luciana; Galdran, Adrian; van Ginneken, Bram; Haase, Robert; Hashimoto, Daniel A.; Hoffman, Michael M.; Huisman, Merel; Jannin, Pierre; Kahn, Charles E.; Kainmueller, Dagmar; Kainz, Bernhard; Karargyris, Alexandros; Karthikesalingam, Alan; Kofler, Florian; Kopp-Schneider, Annette; Kreshuk, Anna; Kurc, Tahsin; Landman, Bennett A.; Litjens, Geert; Madani, Amin; Maier-Hein, Klaus; Martel, Anne L.; Mattson, Peter; Meijering, Erik; Menze, Bjoern; Moons, Karel G. M.; Müller, Henning; Nichyporuk, Brennan; Nickel, Felix; Petersen, Jens; Rajpoot, Nasir; Rieke, Nicola; Saez-Rodriguez, Julio; Sánchez, Clara I.; Shetty, Shravya; van Smeden, Maarten; Summers, Ronald M.; Taha, Abdel A.; Tiulpin, Aleksei; Tsaftaris, Sotirios A.; Van Calster, Ben; Varoquaux, Gaël; Jäger, Paul F. (2024). Metrics reloaded: recommendations for image analysis validation. 17 p. Nature Methods. Vol. 21.
https://doi.org/10.1038/s41592-023-02151-z

Reinke, Annika; Tizabi, Minu D.; Baumgartner, Michael; Eisenmann, Matthias; Heckmann-Nötzel, Doreen; Kavur, A. Emre; Rädsch, Tim; Sudre, Carole H.; Acion, Laura; Antonelli, Michela; Arbel, Tal; Bakas, Spyridon; Benis, Arriel; Buettner, Florian; Cardoso, M. Jorge; Cheplygina, Veronika; Chen, Jianxu; Christodoulou, Evangelia; Cimini, Beth A.; Farahani, Keyvan; Ferrer, Luciana; Galdran, Adrian; van Ginneken, Bram; Glocker, Ben; Godau, Patrick; Hashimoto, Daniel A.; Hoffman, Michael M.; Huisman, Merel; Isensee, Fabian; Jannin, Pierre; Kahn, Charles E.; Kainmueller, Dagmar; Kainz, Bernhard; Karargyris, Alexandros; Kleesiek, Jens; Kofler, Florian; Kooi, Thijs; Kopp-Schneider, Annette; Kozubek, Michal; Kreshuk, Anna; Kurc, Tahsin; Landman, Bennett A.; Litjens, Geert; Madani, Amin; Maier-Hein, Klaus; Martel, Anne L.; Meijering, Erik; Menze, Bjoern; Moons, Karel G. M.; Müller, Henning; Nichyporuk, Brennan; Nickel, Felix; Petersen, Jens; Rafelski, Susanne M.; Rajpoot, Nasir; Reyes, Mauricio; Riegler, Michael ; Rieke, Nicola; Saez-Rodriguez, Julio; Sánchez, Clara I.; Shetty, Shravya; Summers, Ronald M.; Taha, Abdel A.; Tiulpin, Aleksei; Tsaftaris, Sotirios A.; Van Calster, Ben; Varoquaux, Gaël; Yaniv, Ziv R.; Jäger, Paul F.; Maier-Hein, Lena (2024). Understanding metric-related pitfalls in image analysis validation. 12 p. Nature Methods. Vol. 21.
https://doi.org/10.1038/s41592-023-02150-0

Ali, Sharib; Ghatwary, Noha; Jha, Debesh; Isik-Polat, Ece; Polat, Gorkem; Yang, Cheng; Li, Wuyang; Galdran, Adrian; Ballester, Miguel Angel Gonzalez; Thambawita, Vajira L B; Hicks, Steven; Poudel, Sahadev; Lee, Sang-Woong; Jin, Ziyi; Gan, Tianyuan; Yu, Chenghui; Yan, JiangPeng; Yeo, Doyeob; Lee, Hyunseok Lee; Tomar, Nikhil Kumar; Haitham, Mahmood; Ahmed, Amr; Riegler, Michael Alexander ; Daul, Christian; Halvorsen, Pål ; Rittscher, Jens; Salem, Osama E.; Lamarque, Dominique; Cannizzaro, Renato; Realdon, Stefano; de Lange, Thomas; East, James E (2024). Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge. Scientific Reports. Vol. 14.
https://doi.org/10.1038/s41598-024-52063-x

Svennevik, Hanna; Hicks, Steven; Riegler, Michael ; Storelvmo, Trude; Hammer, Hugo Lewi (2024). A dataset for predicting cloud cover over Europe. 6 p. Scientific Data. Vol. 11.
https://doi.org/10.1038/s41597-024-03062-0

Monakhov, Vladimir; Thambawita, Vajira L B; Halvorsen, Pål ; Riegler, Michael (2023). GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos. Sensors. Vol. 23:2087.
https://doi.org/10.3390/s23042087

Machacek, Roman; Mozaffari, Leila; Sepasdar, Zahra; Parasa, Sravanthi; Halvorsen, Pål ; Riegler, Michael ; Thambawita, Vajira L B (2023). Mask-conditioned latent diffusion for generating gastrointestinal polyp images. Habault, Guillaume; Dao, Minh-Son; Riegler, Michael; Dang Nguyen, Duc Tien; Nakashima, Yuta; Gurrin, Cathal (Ed.). ICDAR’23: Proceedings of the 4th ACM Workshop on Intelligent Cross-Data Analysis and Retrieval. Association for Computing Machinery (ACM).
https://doi.org/10.1145/3592571.3592978

Storås, Andrea; Fineide, Fredrik; Magnø, Morten Schjerven; Thiede, Bernd; Chen, Xiangjun; Strumke, Inga; Halvorsen, Pål ; Galtung, Hilde; Jensen, Janicke Cecilie Liaaen; Utheim, Tor Paaske ; Riegler, Michael Alexander (2023). Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction. Scientific Reports. Vol. 13.
https://doi.org/10.1038/s41598-023-50342-7

Thambawita, Vajira L B; Storås, Andrea; Hicks, Steven; Halvorsen, Pål ; Riegler, Michael (2023). MLC at HECKTOR 2022: The Effect and Importance of Training Data When Analyzing Cases of Head and Neck Tumors Using Machine Learning. Andrearczyk, Vincent; Oreiller, Valentin; Hatt, Mathieu; Depeursinge, Adrien (Ed.). Head and Neck Tumor Segmentation and Outcome Prediction . Springer Nature.
https://doi.org/https://doi.org/10.1007/978-3-031-

Research reports

Thambawita, Vajira; Jha, Debesh; Riegler, Michael ; Halvorsen, Pål ; Hammer, Hugo Lewi ; Johansen, Håvard D.; Johansen, Dag (2018). The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract using Global Features and Deep Learning. 3 p. MediaEval 2018, arXiv:1810.13278, Cornell University.

Dang Nguyen, Duc Tien; Riegler, Michael (2018). GameStory Task at MediaEval 2018. 3 p. CEUR Workshop Proceedings.

Dissemination

Riegler, Michael (2023). KI og kunstig befruktning.

Riegler, Michael ; Lison, Pierre; Falkum, Ingrid Lossius (2023). Kunstig intelligens-modeller er ikke miniatyr­versjoner av den menneskelige hjernen. Forskersonen.no.

Sareen, Siddharth; Riegler, Michael ; Reinertsen, Hilde (2023). Hvordan vil kunstig intelligens forme verden de neste ti årene?.
https://www.morgenbladet.no/aktuelt/2023/01/26/hvo

Riegler, Michael (2023). Sperm-tracking, use of a human sperm dataset. Workshop in Spermatology. OsloMet.

Riegler, Michael (2023). Automatic Tracking of the ICSI procedure using Deep Learning. Workshop in Spermatology. OsloMet.

Riegler, Michael Alexander ; Reinertsen, Hilde; Sareen, Siddharth (2023). Hvordan vil kunstig intelligens forme verden de neste ti årene?. Morgenbladet.

Chatterjee, Ayan; Pahari, Nibedita; Prinz, Andreas; Riegler, Michael (2023). Author Correction: Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation (Scientific Reports, (2022), 12, 1, (19825), 10.1038/s41598-022-24118-4). Scientific Reports. Vol. 13.
https://doi.org/10.1038/s41598-023-30029-9

Habault, Guillaume; Dao, Minh-Son; Riegler, Michael ; Dang Nguyen, Duc Tien; Nakashima, Yuta; Gurrin, Cathal (2023). ICDAR’23: Intelligent Cross-Data Analysis and Retrieval. Habault, Guillaume; Dao, Minh-Son; Riegler, Michael; Dang Nguyen, Duc Tien; Nakashima, Yuta; Gurrin, Cathal (Ed.). ICDAR’23: Proceedings of the 4th ACM Workshop on Intelligent Cross-Data Analysis and Retrieval. p. 674-675. Association for Computing Machinery (ACM).
https://doi.org/https://doi.org/10.1145/3591106.35

Storås, Andrea; Fineide, Fredrik; Hammer, Hugo Lewi ; Khan, Ayyad Ahmad Zartasht; Magnø, Morten Schjerven; Chen, Xiangjun; Halvorsen, Pål ; Utheim, Tor Paaske ; Riegler, Michael Alexander (2023). Using explainable artificial intelligence (XAI) to explore factors affecting meibomian gland (MG) dropout. Investigative Ophthalmology and Visual Science.

Fineide, Fredrik; Storås, Andrea; Magnø, Morten Schjerven; Hammer, Hugo Lewi ; Chen, Xiangjun; Khan, Ayyad Ahmad Zartasht; Halvorsen, Pål ; Utheim, Tor Paaske ; Riegler, Michael Alexander (2023). Predicting the degree of meibomian gland dropout with artificial intelligence. Investigative Ophthalmology and Visual Science.