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
MELBA–BVM 2025 Special Issue
Maximilian WeihererVisual Computing Erlangen, Friedrich-Alexander-Universtität Erlangen-Nürnberg, Erlangen, Germany
Regensburg Medical Image Computing (ReMIC), OTH Regensburg, Regensburg, Germany, Antonia von RiedheimDepartment for Plastic, Hand and Reconstructive Surgery, University Hospital Regensburg, Regensburg, Germany, Vanessa BrébantDepartment for Plastic, Hand and Reconstructive Surgery, University Hospital Regensburg, Regensburg, Germany, Bernhard EggerVisual Computing Erlangen, Friedrich-Alexander-Universtität Erlangen-Nürnberg, Erlangen, Germany, Christoph PalmRegensburg Medical Image Computing (ReMIC), OTH Regensburg, Regensburg, Germany
AIxCell: A Domain-Specific and Meta-Learning based AutoML System for Cellular Image Segmentation
2026/02/16February 2026 issue
Jan-Henner RobergAICOS, Fraunhofer Portugal Research, Lars LeyendeckerProduction Quality, Fraunhofer Institute for Production Technology IPT, Sebastian SchönlebenProduction Quality, Fraunhofer Institute for Production Technology IPT, Robert H. SchmittProduction Quality, Fraunhofer Institute for Production Technology IPT
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University
Benchmarking Foundation Models for Mitotic Figure Classification
2026/01/30MELBA–BVM 2025 Special Issue
Jonas AmmelingTechnische Hochschule Ingolstadt, AImotion, Ingolstadt, DE, Jonathan GanzMIRA vision Microscopy GmbH, Göppingen, DE
Technische Hochschule Ingolstadt, AImotion, Ingolstadt, DE, Emely RosbachTechnische Hochschule Ingolstadt, AImotion, Ingolstadt, DE, Ludwig LausserTechnische Hochschule Ingolstadt, AImotion, Ingolstadt, DE, Christof A. BertramUniversity of Veterinary Medicine, Institute of Pathology, Vienna, AU, Katharina BreiningerCenter for AI and Data Science, Julius-Maximilians-Universität Würzburg, Würzburg, DE
Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, DE, Marc AubrevilleFlensburg University of Applied Sciences, Flensburg, DE
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