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
The Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods
2025/12/05December 2025 issue
Akis LinardosDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USAAkis LinardosDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
Center for Federated Learning in Medicine, Indiana University School of Medicine, Indianapolis, IN, USA et al.
Center for Federated Learning in Medicine, Indiana University School of Medicine, Indianapolis, IN, USA, Sarthak PatiDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
Center for Federated Learning in Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
Medical AI Group, MLCommons, San Francisco, CA, USA, Ujjwal BaidDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
Center for Federated Learning in Medicine, Indiana University School of Medicine, Indianapolis, IN, USA, Brandon EdwardsIntel Corporation, Santa Clara, CA, USA, Patrick FoleyIntel Corporation, Santa Clara, CA, USA, Kevin TaIntel Corporation, Santa Clara, CA, USA, Verena ChungSage Bionetworks, Seattle, WA, USA, Micah ShellerMedical AI Group, MLCommons, San Francisco, CA, USA
Intel Corporation, Santa Clara, CA, USA, Muhammad Irfan KhanTurku University of Applied Sciences, Turku, Finland, Mojtaba JafaritadiStanford University, Stanford, CA, USA, Elina KontioTurku University of Applied Sciences, Turku, Finland, Suleiman KhanTurku University of Applied Sciences, Turku, Finland, Leon MächlerEcole Normale Supérieure, Paris, France, Ivan EzhovTechnical University of Munich, Munich, Germany, Suprosanna ShitTechnical University of Munich, Munich, Germany, Johannes C. PaetzoldWeill Cornell Medicine, New York, USA, Gustav GrimbergEzri AI Labs, Paris, France, Manuel A. NickelTechnical University of Munich, Munich, Germany, David NaccacheEcole Normale Supérieure, Paris, France, Vasilis SiomosCity St George’s, University of London, UK, Jonathan Passerat-PalmbachImperial College London, London, UK, Giacomo TarroniCity St George’s, University of London, UK
Imperial College London, London, UK, Daewoon KimSeoul National University, Seoul, South Korea, Leonard L. KlausmannOstbayerische Technische Hochschule (OTH) Regensburg, Germany, Prashant ShahIntel Corporation, Santa Clara, CA, USA, Bjoern MenzeUniversität Zürich, Zürich, Switzerland, Dimitrios MakrisKingston University London, London, UK, Spyridon BakasDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
Center for Federated Learning in Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
Medical AI Group, MLCommons, San Francisco, CA, USA
Kingston University London, London, UK
Departments of Radiology and Imaging Sciences; Neurological Surgery; Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
Department of Computer Science, Luddy School of Informatics, Computing and Engineering, Indiana University, Indianapolis, IN, USA
Data Exfiltration by Compression Attack: Definition and Evaluation on Medical Image Data
2025/12/05December 2025 issue
Huiyu LIResearch Centre Inria Sophia Antipolis - Méditerranée, Nicholas AyacheResearch Centre Inria Sophia Antipolis - Méditerranée, Hervé DelingetteResearch Centre Inria Sophia Antipolis - Méditerranée
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