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
A schistosomiasis dataset with bright- and darkfield images
2025/12/31Special Issue on Open Data at MICCAI 2024–2025
Dieudonné K. SiluéUFR Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire.Dieudonné K. SiluéUFR Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire.
Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan Côte d’Ivoire. et al.
Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan Côte d’Ivoire., María Díaz de León DerbyDepartment of Bioengineering, University of California, Berkeley, Berkeley, California., Charles B. DelahuntGlobal Health Labs, Inc, Bellevue, Washington., Anne-Laure Le NyGlobal Health Labs, Inc, Bellevue, Washington., Ethan SpencerGlobal Health Labs, Inc, Bellevue, Washington., Maxim ArmstrongDepartment of Bioengineering, University of California, Berkeley, Berkeley, California., Karla N. FisherDivision of General Internal Medicine, Toronto General Hospital, University Health Network, Toronto, Canada.
Division of Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, Canada., Daniel A. FletcherDepartment of Bioengineering, University of California, Berkeley, Berkeley, California.
Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, Berkeley, California.
Chan Zuckerberg Biohub, San Francisco, California., Isaac I. BogochDivision of General Internal Medicine, Toronto General Hospital, University Health Network, Toronto, Canada.
Division of Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, Canada.
Department of Medicine, University of Toronto, Toronto, Canada., Jean T. CoulibalyUFR Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire.
Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan Côte d’Ivoire.
The Trauma THOMPSON Dataset for Real-World Emergency AI
2025/12/31Special Issue on Open Data at MICCAI 2024–2025
Yupeng ZhuoPurdue University, West Lafayette, IN, USA, Eddie ZhangPurdue University, West Lafayette, IN, USA, Xiangchen YuPurdue University, West Lafayette, IN, USA, Aditya PachpandePurdue University, West Lafayette, IN, USA, Andrew W. KirkpatrickUniversity of Calgary, Calgary, Alberta, Canada, Kyle CouperusThe Geneva Foundation, Tacoma, WA, USA, Jessica MckeeUniversity of Calgary, Calgary, Alberta, Canada, Juan WachsPurdue University, West Lafayette, IN, USA
Special Issue on Open Data at MICCAI 2024–2025
Nikita BediDivision of Head & Neck Surgery, Department of Otolaryngology, Stanford University, Anita RauDepartment of Biomedical Data Science, Stanford University, Alberto PadernoDepartment of Otolaryngology–Head and Neck Surgery, Humanitas Research Hospital, Hlu VangDivision of Head & Neck Surgery, Department of Otolaryngology, Stanford University, Yoon Kyoung SoDivision of Head & Neck Surgery, Department of Otolaryngology, Stanford University, F.~Christopher HolsingerDivision of Head & Neck Surgery, Department of Otolaryngology, Stanford University
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