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
Predicting gestational age at birth in the context of preterm birth from multi-modal fetal MRI
2026/06/05June 2026 issue
Diego Fajardo-RojasEarly Life Imaging department, King’s College London, London, UK
Biomedical Computing department, King’s College London, London, UK, Megan HallEarly Life Imaging department, King’s College London, London, UK
Women’s Health department, School of Life Course and Population Sciences, King’s College London, London, UK, Daniel CrombEarly Life Imaging department, King’s College London, London, UK, Mary A. RutherfordEarly Life Imaging department, King’s College London, London, UK, Lisa StoryEarly Life Imaging department, King’s College London, London, UK
Women’s Health department, School of Life Course and Population Sciences, King’s College London, London, UK, Emma RobinsonBiomedical Computing department, King’s College London, London, UK, Jana HutterInstitute for Information Processing, Leibniz University Hannover, Hannover, Germany
Early Life Imaging department, King’s College London, London, UK
Generalized TV–ℓp Structured Priors for Bayesian T1 Mapping
2026/06/01UNSURE2025 special issue
Disi LinDepartment of Computing Science, Umeå University, Sweden, Martin BerggrenDepartment of Computing Science, Umeå University, Sweden, Tommy LöfstedtDepartment of Computing Science, Umeå University, Sweden
Effect of Demographic Bias on Skin Lesion Classification
2026/05/29Special issue on FAIMI
Ralf RaumannsFontys University of Applied Science, Venlo, The Netherlands
Eindhoven University of Technology, Eindhoven, The Netherlands
IT University of Copenhagen, Denmark, Gerard SchoutenFontys University of Applied Science, Eindhoven, The Netherlands, Veronika CheplyginaIT University of Copenhagen, Denmark, Josien P.W. PluimEindhoven University of Technology, Eindhoven, The Netherlands
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