Research

My research develops robust and trustworthy deep learning for medical image analysis — spanning spine and cardiac MRI, multimodal biomedical data, and uncertainty quantification. I work at the intersection of computer vision and machine learning for healthcare, building methods that are reliable, calibrated, and reproducible in clinical practice.
Medical Image Analysis Computer Vision Trustworthy Deep Learning Uncertainty Quantification Machine Learning for Healthcare

Publications

Patents

Granted patent

  1. Patent Giese D., Wetzl J., Maria Monzon, Fischer C., Yoon S.S. (2025). Automatic Determination of a Motion Parameter of the Heart. U.S. Patent No. 12,239,477 B2 — Siemens Healthineers AG.
    Google Patents Project

First-Author Publications

Work I led as first, shared-first or senior author

  1. Conference paper Maria Monzon, Andrew Zisserman, Robin Y. Park, Catherine R. Jutzeler, Amir Jamaludin (2026). Be Indiscrete: The Benefits of Learning Continuous Spine Degeneration Severity Scores. Medical Image Computing and Computer Assisted Intervention (MICCAI).
    Code
  2. Conference paper Palau B., Vogt F., Laslo D., Li H., Konukoglu E., Maria Monzon*, Jutzeler C.R.* (2026). Beyond Fluency: A Clinical Benchmark and Anomaly-Enhanced Baseline for Spine MRI Report Generation. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops — CV4Clinic.
    Link
  3. Conference paper Maria Monzon, Jamaludin A., Jutzeler C.R., Zisserman A. (2026). Segmentation Pre-Training for Efficient Spine Degeneration Grading. MICCAI Workshop on Efficient Medical AI (EMA) — under review.
  4. Journal paper Brenzikofer A.*, Maria Monzon*, Galbusera F., Manjaly Z.M., Cina A., Jutzeler C.R. (2026). Uncertainty Quantification of Central Canal Stenosis Deep Learning Classifier From Lumbar Sagittal T2-Weighted MRI. JOR Spine.
    Link Code Project DOI
  5. Journal paper Maria Monzon, De Schoenmacker I., Cina A., Enz R., Lanz C., Galbusera F., Jutzeler C.R., Manjaly Z.M. (2025). A data-driven analysis of lumbar steroid injection satisfaction in patients with chronic low back pain. Scientific Reports, 15(1).
    Link Code Project DOI
  6. Conference paper Maria Monzon*, Iff T.*, Konukoglu E., Jutzeler C.R. (2025). Enhancing Low Back Pain Assessment with Diffusion Models for Lumbar Spine MRI Segmentation. Proceedings of Machine Learning Research (PMLR), 301, 1145–1163 (MIDL).
    Paper (PMLR) PDF Project page Code Project

Contributing Author

Collaborative work as a contributing co-author

  1. Journal paper De Schoenmacker I., Maria Monzon, Sirucek L., Scheuren P.S., Lütolf R., Gorrell L.M., Brunner F., Curt A., Rosner J., Schweinhardt P., Hubli M., Jutzeler C.R. (2026). The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions. Scientific Reports, 2026.
    Link DOI
  2. Journal paper Laslo D., Wolleb J., Maria Monzon, Kottke R., Sirin S., Müller T., Suhami D. (2026). Generative AI for spatial tumor growth on MRI: a proof-of-principle study in pediatric diffuse midline glioma. BMC Medicine.
    Link DOI
  3. Journal paper Bonaretti S., …, Maria Monzon, … (ORMIR community, 44 authors) (2026). Open and reproducible research in musculoskeletal imaging: Why it matters and how to implement it with the guidelines of the ORMIR community. JBMR Plus, 10(4), ziag025.
    Link DOI
  4. Journal paper Cina A., Maria Monzon, Galbusera F., Jutzeler C.R. (2026). Quantifying central canal stenosis prediction uncertainty in SpineNet with conformal prediction. Scientific Reports, 16(1), 4963.
    Link DOI
  5. Journal paper Santini F., Maria Monzon, Poncioni S., Bonaretti S., Hirvasniemi J., Froeling M. (2026). ORMIR-MIDS: An open standard for curating and sharing musculoskeletal imaging data. JBMR Plus, 10(3), ziag013.
    Link Code Project DOI
  6. Journal paper Bereciartua-Pérez A., Maria Monzon, Múgica D., De Both G., Baert J., Hedges B. (2024). Estimation of flea beetle damage in the field using a multistage deep learning-based solution. Artificial Intelligence in Agriculture, 13.
    Link PDF DOI
  7. Journal paper Yoon S.S., Fischer C., Amsel D., Maria Monzon, Toupin S., Pezel T., Garot J. (2023). Fully automated AI-based cardiac motion parameter extraction — application to mitral and tricuspid valves on long-axis cine MR images. European Journal of Radiology, 166.
    Link DOI

Selected Conferences

Selected talks, posters and conference abstracts

  1. Lightning Talk Maria Monzon (2026). Be Indiscrete: The Benefits of Learning Continuous Spine Degeneration Severity Scores. SAIMI — Symposium on AI in Medical Imaging — Lightning Talk.
  2. Poster Maria Monzon, Iff T., Konukoglu E., Jutzeler C. (2024). Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients. Machine Learning for Health (ML4H) — Poster.
  3. Poster Maria Monzon, Iff T., Manjaly Z.M., Jutzeler C.R. (2024). A Fully Automated Pipeline for Extracting Vertebral Compression Parameters from Clinical MRI Scans. IEEE International Symposium on Biomedical Imaging (ISBI) — Poster.
  4. Conference Maria Monzon, Yoon S.S., Fischer C., Maier A., Wetzl J., Giese D. (2021). Fully automatic extraction of mitral valve annulus motion parameters on long-axis CINE CMR using deep learning. International Society for Magnetic Resonance in Medicine (ISMRM), 29th Annual Meeting.
    Abstract (ISMRM) Summary Report Project