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
April 2026 issue
Gaurav RudravaramDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA, Shunxing BaoDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA, Lucas W. RemediosDepartment of Computer Science, Vanderbilt University, Nashville, TN, USA, Aravind R. KrishnanDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA, Michael E. KimDepartment of Computer Science, Vanderbilt University, Nashville, TN, USA, Yihao LiuDepartment of Computer Science, Vanderbilt University, Nashville, TN, USA, Chenyu GaoDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA, Rendong ZhangDepartment of Computer Science, Vanderbilt University, Nashville, TN, USA, Bohan JiangDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA, Qi LiuCenter for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, TN, USAGaurav RudravaramDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA et al.
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, USA, Ken S LauCenter for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
Vanderbilt Center for Mucosal Inflammation and Cancer, Vanderbilt University Medical Center, Nashville, TN, USA
Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA
Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA, Joseph T. RolandEpithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA, Mary K. WashingtonDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA, Lori A. CoburnVanderbilt Center for Mucosal Inflammation and Cancer, Vanderbilt University Medical Center, Nashville, TN, USA
Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
Program in Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
Veterans Affairs Tennessee Valley Healthcare System, Nashville, TN, USA, Keith T. WilsonVanderbilt Center for Mucosal Inflammation and Cancer, Vanderbilt University Medical Center, Nashville, TN, USA
Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
Program in Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
Veterans Affairs Tennessee Valley Healthcare System, Nashville, TN, USA
Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA, Yuankai HuoDepartment of Computer Science, Vanderbilt University, Nashville, TN, USA, Bennett A. LandmanDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
Department of Computer Science, Vanderbilt University, Nashville, TN, USA
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
From Prompts to Pipelines: Evaluating LLM-Generated Medical Image Segmentation Baselines
2026/03/27MELBA–BVM 2025 Special Issue
Jasmin ArjomandiDepartment Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, Luisa NeubigDepartment Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, Franziska Mathis-UllrichDepartment Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, Andreas M. KistDepartment Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
Biophysics-Enhanced Neural Representations for Patient-Specific Respiratory Motion Modeling
2026/03/22MELBA–BVM 2025 Special Issue
Jan BoysenGerman Research Center for Artificial Intelligence (DFKI), Lübeck, DE, Hristina UzunovaClinic for Orthopedics and Orthopedic Surgery, University Medicine Greifswald, Greifswald, DE, Heinz HandelsGerman Research Center for Artificial Intelligence (DFKI), Lübeck, DE
Institute of Medical Informatics, University of Lübeck, DE, Jan EhrhardtGerman Research Center for Artificial Intelligence (DFKI), Lübeck, DE
Institute of Medical Informatics, University of Lübeck, 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