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.
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
June 2025 issue
Anahita Fathi KazerooniCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Nastaran KhaliliCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Xinyang LiuSheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital, Washington DC, USA, Debanjan HaldarDepartment of Neurosurgery, Thomas Jefferson University Hospital, PA, USA, Zhifan JiangSheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital, Washington DC, USA, Anna ZapaishchykovaDana-Farber Brigham Cancer Center & Boston Children’s Hospital, Boston, MA, USA, Julija PavaineDepartment of Paediatric Radiology, Royal Manchester Children’s Hospital, Manchester University Hospitals NHS Foundation Trust, University of Manchester, Manchester, UK, Lubdha M. ShahUniversity of Utah, UT, USA, Blaise V. JonesCincinnati Children’s Hospital Medical Center, OH, USA, Nakul ShethDepartment of Radiology, The Children’s Hospital of Philadelphia, PA, USA, Sanjay P. PrabhuDivision of Neuroradiology, Department of Radiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA, Aaron S. McAllisterDepartment of Radiology, Nationwide Children’s Hospital, OH, USA, Wenxin TuCollege of Arts and Sciences, University of Pennsylvania, PA, USA, Khanak K. NandoliaDepartment of Diagnostic and Interventional Radiology, All India Institute of Medical Sciences, Rishikesh, India, Andres F. RodriguezDepartment of Diagnostic & Interventional Imaging, Neuroradiology section, The University of Texas Health at Houston, Texas, USA, Ibraheem Salman ShaikhBeth Israel Deaconess Medical Center, Harvard Medical School, MA, USA, Mariana Sanchez-MontanoUNIDAD DE PATOLOGIA CLINICA:Guadalajara, JALISCO, Mexico, Hollie Anne LaiDepartment of Radiology, Children’s Health Orange County, CA, USA, Maruf AdewoleMedical Artificial Intelligence (MAI) Lab, Crestview Radiology, Lagos, Nigeria, Jake AlbrechtSage Bionetworks, USA, Udunna AnazodoMontreal Neurological Institute (MNI), McGill University, Montreal, QC, Canada, Hannah AndersonDepartment of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA, Syed Muhammed AnwarSheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital, Washington DC, USA, Alejandro AristizabalMLCommons, USA, Sina BagheriDepartment of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA, Ujjwal BaidDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA, Timothy BergquistSage Bionetworks, USA, Austin J. BorjaDepartment of Neurosurgery at the University of Southern California, CA, USA, Evan CalabreseDepartment of Radiology, Duke University Medical Center, Durham, NC, USA, Verena ChungSage Bionetworks, USA, Gian-Marco ConteMayo Clinic, MN, USA, James EddySage Bionetworks, USA, Ivan EzhovDepartment of Informatics, Technical University Munich, Germany, Ariana M. FamiliarCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Keyvan FarahaniNational Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Deep GandhiCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Anurag GottipatiCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Shuvanjan HaldarBiomedical Engineering Rutgers University, New Brunswick, NJ, USA, Juan Eugenio IglesiasAthinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA, Anastasia JanasYale University, New Haven, CT, USA, Elaine ElainePrecisionFDA, U.S. Food and Drug Administration, Silver Spring, MD, USA, Alexandros KarargyrisMLCommons, USA, Hasan KassemMLCommons, USA, Neda KhaliliCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Florian KoflerHelmholtz AI, Helmholtz Munich, Germany, Dominic LaBellaDepartment of Radiation Oncology, Duke University Medical Center, Durham, NC, USA, Koen Van LeemputDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark, Hongwei B. LiAthinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA, Nazanin MalekiYale University, New Haven, CT, USA, Zeke MeierBooz Allen Hamilton, McLean, VA, USA, Bjoern MenzeBiomedical Image Analysis & Machine Learning, Department of Quantitative Biomedicine, University of Zurich, Switzerland, Ahmed W. MoawadMercy Catholic Medical Center, Darby, PA, USA, Sarthak PatiMLCommons, USA, Marie PiraudHelmholtz AI, Helmholtz Munich, Germany, Tina PoussaintDana-Farber Brigham Cancer Center & Boston Children’s Hospital, Boston, MA, USA, Zachary J. ReitmanDepartment of Radiation Oncology, Duke University Medical Center, Durham, NC, USA, Jeffrey D. RudieUniversity of San Diego, CA, USA, Rachit SalujaCornell University, Ithaca, NY, USA, MIcah ShellerMLCommons, USA, Russell Takeshi ShinoharaStatistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA, Karthik ViswanathanCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Chunhao WangDepartment of Radiation Oncology, Duke University Medical Center, Durham, NC, USA, Benedikt WiestlerDepartment of Neuroradiology, Technical University of Munich, Munich, Germany, Walter F. WigginsGreensboro Radiology, Greensboro, NC, USA, Christos DavatzikosCenter for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA, Phillip B. StormCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Miriam BornhorstBrain Tumor Institute, Children’s National Hospital, Washington, DC, USA, Roger PackerBrain Tumor Institute, Children’s National Hospital, Washington, DC, USA, Trent HummelBrain Tumor Center, Cincinnati Children’s Hospital, Cincinnati, OH, USA, Peter de BlankBrain Tumor Center, Cincinnati Children’s Hospital, Cincinnati, OH, USA, Lindsey HoffmanCenter for Cancer and Blood Disorders, Phoenix Children’s Hospital, Phoenix, AZ, US, Mariam AboianDepartment of Radiology, The Children’s Hospital of Philadelphia, PA, USA, Ali NabavizadehCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Jeffrey B. WareCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Benjamin H. KannDana-Farber Brigham Cancer Center & Boston Children’s Hospital, Boston, MA, USA, Brian RoodCenter for Cancer and Blood Disorders, Children’s National Hospital, Washington, DC, USA, Adam ResnickCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA, Spyridon BakasDivision of Computational Pathology, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA, Arastoo VossoughDepartment of Radiology, The Children’s Hospital of Philadelphia, PA, USA, Marius George LinguraruSheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital, Washington DC, USAAnahita Fathi KazerooniCenter for Data-Driven Discovery in Biomedicine (D3b), The Children’s Hospital of Philadelphia, PA, USA et al.
Understanding differences in applying DETR to natural and medical images
2025/05/30May 2025 issue
Yanqi XuCenter for Data Science, New York Univeristy, New York, NY, USA, Yiqiu ShenNYU Grossman School of Medicine, New York, NY, USA, Carlos Fernandez-GrandaCenter for Data Science, New York Univeristy, New York, NY, USA, Laura HeacockNYU Langone Health, New York, NY, USA, Krzysztof J. GerasNYU Grossman School of Medicine, New York, NY, USA
BrainMorph: A Foundational Keypoint Model for Robust and Flexible Brain MRI Registration
2025/05/27May 2025 issue
Alan Q. WangDepartment of Radiology, Weill Cornell Medicine, New York City, NY, USA, Rachit SalujaDepartment of Radiology, Weill Cornell Medicine, New York City, NY, USA, Heejong KimDepartment of Radiology, Weill Cornell Medicine, New York City, NY, USA, Xinzi HeDepartment of Radiology, Weill Cornell Medicine, New York City, NY, USA, Adrian DalcaComputer Science and Artificial Intelligence Lab at the Massachusetts Institute of Technology, Cambridge, MA, USA, Mert R. SabuncuSchool of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
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