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
August 2024 issue
Nancy R. NewlinDepartment of Computer Science, Vanderbilt University, Nashville, TN, Kurt SchillingDepartment of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Serge KoudoroIndiana University Bloomington, Bloomington, IN, Bramsh Qamar ChandioMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, Praitayini KanakarajDepartment of Computer Science, Vanderbilt University, Nashville, TN, Daniel MoyerDepartment of Computer Science, Vanderbilt University, Nashville, TN, Claire E. KellyDevelopmental Imaging, Murdoch Children’s Research Institute, Melbourne, AustraliaNancy R. NewlinDepartment of Computer Science, Vanderbilt University, Nashville, TN et al.
Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, Australia
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia, Sila GencDevelopmental Imaging, Murdoch Children’s Research Institute, Melbourne, Australia
Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, Royal Children’s Hospital, Melbourne, Australia, Jian ChenDevelopmental Imaging, Murdoch Children’s Research Institute, Melbourne, Australia, Joseph Yuan-Mou YangDevelopmental Imaging, Murdoch Children’s Research Institute, Melbourne, Australia
Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, Royal Children’s Hospital, Melbourne, Australia
Neuroscience Research, Murdoch Children’s Research Institute, Melbourne, Australia
Department of Pediatrics, University of Melbourne, Melbourne, Australia, Ye WuSchool of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China, Yifei HeSchool of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China, Jiawei ZhangCollege of Information Engineering, Zhejiang University of Technology, Hangzhou, China, Qingrun ZengSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China, Fan ZhangSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China, Nagesh AdluruWaisman Center, Department of Radiology, University of Wisconsin, Madison, Vishwesh NathNVIDIA, Nashville, TN, USA, Sudhir PathakLearning Research and Development Center, University of Pittsburgh, Walter SchneiderLearning Research and Development Center, University of Pittsburgh, Anurag GadeBrigham and Women’s Hospital, Boston, Yogesh RathiBrigham and Women’s Hospital, Harvard Medical School, Boston, Tom HendriksDepartment of Computer Science and Mathematics, Eindhoven University of Technology, Netherlands, Anna VilanovaDepartment of Computer Science and Mathematics, Eindhoven University of Technology, Netherlands, Maxime ChamberlandDepartment of Computer Science and Mathematics, Eindhoven University of Technology, Netherlands, Tomasz PieciakLPI, ETSI Telecomunicación, Universidad de Valladolid, Castilla y León, Spain
Sano Centre for Computational Medicine, 30-054 Kraków, Poland, Dominika CiupekSano Centre for Computational Medicine, 30-054 Kraków, Poland, Antonio Tristán-VegaLPI, ETSI Telecomunicación, Universidad de Valladolid, Castilla y León, Spain, Santiago Aja-FernándezLPI, ETSI Telecomunicación, Universidad de Valladolid, Castilla y León, Spain, Maciej MalawskiSano Centre for Computational Medicine, 30-054 Kraków, Poland, Gani OuedraogoAix-Marseille Université, Marseille, France, Julia MachnioSano Centre for Computational Medicine, 30-054 Kraków, Poland, Paul M. ThompsonMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, Neda JahanshadMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, Eleftherios GaryfallidisIndiana University Bloomington, Bloomington, IN, Bennett A. LandmanDepartment of Computer Science, Vanderbilt University, Nashville, TN
Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation
2024/08/31August 2024 issue
Prerak ModyDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands
HollandPTC consortium – Erasmus Medical Center, Rotterdam, Holland Proton Therapy Centre, Delft, Leiden
University Medical Center, Leiden and TU Delft, Delft, The Netherlands, Nicolas F. Chaves-de-PlazaComputer Graphics and Visualization Group , EEMCS, TU Delft, Delft, The Netherlands, Chinmay RaoDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands, Eleftheria AstrenidouDepartment of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands, Mischa de RidderDepartment of Radiation Oncology, University Medical Center, Utrecht, The Netherlands, Nienke HoekstraDepartment of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands, Klaus HildebrandtComputer Graphics and Visualization Group , EEMCS, TU Delft, Delft, The Netherlands, Marius StaringDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands
Department of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands
MICCAI 2023 LNQ challenge special issue
Litingyu WangUniversity of Electronic Science and Technology of China, Chengdu, China, Yijie QuUniversity of Electronic Science and Technology of China, Chengdu, China, Xiangde LuoUniversity of Electronic Science and Technology of China, Chengdu, China
Shanghai AI Laboratory, Shanghai, China, Wenjun LiaoUniversity of Electronic Science and Technology of China, Chengdu, China
Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Chengdu, China, Shichuan ZhangUniversity of Electronic Science and Technology of China, Chengdu, China
Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Chengdu, China, Guotai WangUniversity of Electronic Science and Technology of China, Chengdu, China
Shanghai AI Laboratory, Shanghai, China
Latest news
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
2024/02/02 – Journal-to-conference track at MIDL 2024
The MELBA board happy to announce that, in partnership with the MIDL foundation, MIDL 2024 will feature a "journal-to-conference" track, inviting recently published* MELBA papers to present their work during the conference. Going forward newly published** papers will have the possibility to present their work at MIDL.
Moreover, the best papers of the conference will be invited to submit a journal extension to a special issue in the MELBA journal.
This will strenghten the ongoing partnership between the MIDL foundation and MELBA board, both of which are strongly committed to Open Science and Open Access.
* This excludes papers that are already an extension of a conference/workshop paper.
** Registration deadline will be communicated at a later date.
2023/05/24 – MELBA special issue on image registration
Motion estimation, shape matching and multimodal fusion are some of the core applications in medical image registration that have seen substantial progress through the advent of deep learning-based technique over recent years. We invite you to submit full papers or extended conference works that extend the knowledge in this emerging research field. Submissions are invited in all areas of learning-based medical image registration.
We kindly invite researchers to contribute their high-quality original articles on these topics to our Special Issue. We will be considering submissions between now and Oct 1, 2023 November 30 2023. When submitting your manuscript, the authors should use the cover letter to indicate their intention to be considered in the special issue. The editorial team will aim to streamline the reviews and return a decision within 4-6 weeks from submission. Final accepted papers will be highlighted in a special issue that will be collectively published in the fall/winter of 2023.
In conjunction with MIDL 2024 in Paris we are planning to provide an automatic presentation slot for all original papers accepted within this special issue if the authors are interested in showcasing their research to this audience as well.
Guest Editors:
- Dr. Veronika Zimmer, TU München, Germany;
- Dr. Alessa Hering, RadboudUMC, Netherlands;
- Dr. Mattias Heinrich, University of Lübeck, Germany.
Edit: The submission deadline has been extended from October 1 to November 30, 2023.