Machine Learning for Biomedical Imaging
Welcome to Melba (Machine Learning for Biomedical Imaging), a web-based journal devoted to the free and unrestricted access of high quality articles in the broad field that bridges machine learning and biomedical imaging. There are no publication charges with MELBA: you wrote it, the community reviewed it, we publish it – no hidden charges and you own your own publication. *
* The Scholastica submission system requires a $10 charge during initial submission. However, we are actively working on removing this as well.
You can read more about the mission statement of the journal, or jump right away to the journal publications. For authors, instructions are available here.
Latest publications
Special issue on FAIMI
Maria GalantyInformatics Institute, University of Amsterdam, The Netherlands
Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, The Netherlands, Björn van der SterDepartment of Anesthesiology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands, Alexander P. VlaarDepartment of Intensive Care, Amsterdam UMC, University of Amsterdam, The Netherlands, Clara I. SánchezInformatics Institute, University of Amsterdam, The Netherlands
Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, The Netherlands
Sketchpose: Learning to Segment Cells with Partial Annotations
2025/08/22August 2025 issue
Clément CazorlaInstitut de Recherche en Informatique de Toulouse (IRIT), Institut de Mathématiques de Toulouse (IMT), Centre de Biologie Intégrative (CBI), Laboratoire de Biologie Moléculaire, Cellulaire et du Développement (MCD), Université de Toulouse, CNRS, Université Toulouse III – Paul Sabatier, Toulouse, France
Imactiv-3D, Centre Pierre Potier, 1 place Pierre Potier, 31100 Toulouse, France, Nathanaël MunierInstitut de Recherche en Informatique de Toulouse (IRIT), Institut de Mathématiques de Toulouse (IMT), Centre de Biologie Intégrative (CBI), Laboratoire de Biologie Moléculaire, Cellulaire et du Développement (MCD), Université de Toulouse, CNRS, Université Toulouse III – Paul Sabatier, Toulouse, France, Renaud MorinImactiv-3D, Centre Pierre Potier, 1 place Pierre Potier, 31100 Toulouse, France, Pierre WeissInstitut de Recherche en Informatique de Toulouse (IRIT), Institut de Mathématiques de Toulouse (IMT), Centre de Biologie Intégrative (CBI), Laboratoire de Biologie Moléculaire, Cellulaire et du Développement (MCD), Université de Toulouse, CNRS, Université Toulouse III – Paul Sabatier, Toulouse, France
SWiFT: Soft-Mask Weight Fine-tuning for Bias Mitigation
2025/08/21Special issue on FAIMI
Junyu YanSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK, Feng ChenSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK, Yuyang XueSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK, Yuning DuSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK, Konstantinos VilourasSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK, Sotirios A. TsaftarisSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK, Steven McDonaghSchool of Engineering, University of Edinburgh, EH9 3FB Edinburgh, UK
Latest news
2025/03/28 – Special issue on Fairness of AI in Medical Imaging (FAIMI)
MELBA is excited to launch a special issue in collaboration with the FAIMI initiative, spotlighting research at the intersection of machine learning, medical imaging, and ethics.This issue invites contributions on:
- Bias assessment in ML for medical imaging
- Definitions and applicability of fairness in clinical contexts
- Healthcare inequalities and bias mitigation
- Ethical, legal, and regliatory considerations
- Causality, dataset bias, and moreWe welcome extended versions of FAIMI workshop papers and new submissions from the community.
2025/03/21 – HTML version of articles available
After staying in a beta state for some time, and leveraging the great work of tools such as LaTeXML, we are now including an HTML version of the articles directly into the paper pages. This is intended to facilitate skimming through articles, notably on phone or tablet.
2024/05/14 – MELBA Symposium on Generative Models
We are thrilled to announce the MELBA Symposium on Generative Models, which will take place on Tuesday, June 11 at 9-11:30 AM EDT, 3-5:30 PM CEST! Join us for an exciting lineup of talks from spotlight papers at MELBA surrounding generative models, machine learning and biomedical imaging. Afterwards, there will be a panel discussion with all speakers moderated by a member of the MELBA board.
Meeting ID: 979 1513 2810
Passcode: 115605