Mauricio Reyes

Associate Professor, ARTORG, Universität Bern

Joined

April 2018

Names

Mauricio Reyes (Preferred)

Emails

****@istb.unibe.ch (Confirmed)

****@med.unibe.ch

****@unibe.ch (Confirmed)

Personal Links

Career & Education History

Associate Professor

ARTORG, Universität Bern (unibe.ch)

2013 – 2026

Advisors, Relations & Conflicts

Postdoc Advisor

Miguel González Ballester

2006 – 2008

PhD Advisor

Nicholas Ayache

2003 – 2005

Expertise

Interpretability of AI

2018 – 2023

Medical Image Segmentation

2006 – 2022

Publications

KEPIL: Knowledge-Enhanced Prompt-Image Learning for Prompt-Robust Disease Detection
Haozhe Luo, Shelley Zixin Shu, Ziyu Zhou, Alexander Poellinger, Robert Berke, Anjany Sekuboyina, Mauricio Reyes
- Submitted to ICLR 2026
- Readers: Everyone
INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning
Shelley Zixin Shu, Aurelie Pahud de Mortanges, Alexander Poellinger, Dwarikanath Mahapatra, Mauricio Reyes
- MICCAI 2024 Workshop UNSURE Submission
- Readers: Everyone
Comparing the Performance of Radiation Oncologists versus a Deep Learning Dose Predictor to Estimate Dosimetric Impact of Segmentation Variations for Radiotherapy
Amith Jagannath Kamath, Zahira Mercado Auf der Maur, Robert Poel, Jonas Willmann, Ekin Ermis, Elena Riggenbach, Nicolaus Andratschke, Mauricio Reyes
- MIDL 2024 Oral
- Readers: Everyone
Metrics Reloaded - A new recommendation framework for biomedical image analysis validation
Annika Reinke, Lena Maier-Hein, Evangelia Christodoulou, Ben Glocker, Patrick Scholz, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael Alexander Riegler, Manuel Wiesenfarth, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, Ali Emre Kavur, Tim Rädsch, Minu D. Tizabi, Laura Acion, Michela Antonelli, Tal Arbel et al. (48 additional authors not shown)
- Published: 09 May 2022, Last Modified: 12 May 2023
- MIDL 2022 Short Papers
- Readers: Everyone
A Multi-criteria Quality Assessment of Automated Alternative Segmentations for Radiation Therapy of Brain Tumor Patients
Amith Jagannath Kamath, Roberto Münger, Robert Poel, Elias Rüfenacht, Alain Jungo, Jonas Willmann, Nicolaus Andratschke, Mauricio Reyes
- 08 Dec 2021 (modified: 16 May 2023)
- Submitted to MIDL 2022
- Readers: Everyone
Common limitations of performance metrics in biomedical image analysis
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, Doreen Heckmann-Nötzel, Fabian Isensee, Pierre Jannin, Charles Kahn, Jens Kleesiek, Tahsin Kurc, Michal Kozubek, Bennett A. Landman et al. (15 additional authors not shown)
- Published: 11 May 2021, Last Modified: 06 Mar 2025
- MIDL 2021 Poster
- Readers: Everyone

Co-Authors

View all 87 co-authors

Mauricio Reyes

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

KEPIL: Knowledge-Enhanced Prompt-Image Learning for Prompt-Robust Disease Detection

INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning

Comparing the Performance of Radiation Oncologists versus a Deep Learning Dose Predictor to Estimate Dosimetric Impact of Segmentation Variations for Radiotherapy

Metrics Reloaded - A new recommendation framework for biomedical image analysis validation

A Multi-criteria Quality Assessment of Automated Alternative Segmentations for Radiation Therapy of Brain Tumor Patients

Common limitations of performance metrics in biomedical image analysis

Co-Authors