Machine Learning for Biomedical Imaging
Welcome to Melba (The Journal of 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
Distributionally Robust Deep Learning using Hardness Weighted Sampling
2022/07/18
Lucas FidonShool of Biomedical Engineering & Imaging Sciences, King's College London, Michael AertsenDepartment of Radiology, University Hospitals Leuven, Thomas DeprestDepartment of Radiology, University Hospitals Leuven, Doaa EmamDepartment of Obstetrics and Gynaecology, University Hospitals Leuven, Frédéric GuffensDepartment of Radiology, University Hospitals Leuven, Nada MuftiSchool of Biomedical Engineering & Imaging Sciences, King’s College London, Esther Van ElslanderDepartment of Radiology, University Hospitals Leuven, Ernst SchwartzDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Michael EbnerSchool of Biomedical Engineering & Imaging Sciences, King’s College London, Daniela PrayerDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Gregor KasprianDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Anna L DavidInstitute for Women’s Health, University College London, Andrew MelbourneSchool of Biomedical Engineering & Imaging Sciences, King’s College London, Sébastien OurselinSchool of Biomedical Engineering & Imaging Sciences, King’s College London, Jan DeprestDepartment of Obstetrics and Gynaecology, University Hospitals Leuven, Georg LangsDepartment of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Tom VercauterenSchool of Biomedical Engineering & Imaging Sciences, King’s College LondonLucas FidonShool of Biomedical Engineering & Imaging Sciences, King's College London et al.
Multi-Atlas Segmentation and Spatial Alignment of the Human Embryo in First Trimester 3D Ultrasound
2022/07/14
Wietske A.P. BastiaansenErasmus MC, Melek RousianErasmus MC, Régine P.M. Steegers-TheunissenErasmus MC, Wiro J. NiessenErasmus MC, Anton H.J. KoningErasmus MC, Stefan KleinErasmus MC
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Quantifying Topology In Pancreatic Tubular Networks From Live Imaging 3D Microscopy
2022/07/05
Kasra ArnavazUniversity of Copenhagen, Denmark, Oswin KrauseUniversity of Copenhagen, Denmark, Kilian ZepfTecnhical University of Denmark, Lyngby, Jakob Andreas BærentzenTecnhical University of Denmark, Lyngby, Jelena M. KrivokapicUniversity of Copenhagen, Denmark, Silja HeilmannUniversity of Copenhagen, Denmark, Pia NyengRoskilde University College, Denmark, Aasa FeragenTecnhical University of Denmark, Lyngby
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2022/07/01 – MELBA-IPMI 2021 special issue
Information Processing in Medical Imaging (IPMI) is one of the longest-running conference series in medical imaging, founded in 1969. [...] IPMI 2021 received 200 valid submissions, of which 59 were accepted for publication at the conference. From these, 29 papers were invited to submit an extended journal version to the first special edition of the MELBA journal associated with an IPMI conference. Out of the invited papers, we received 11 submissions, which all underwent a new peer-review process. [...] These papers cover the topics discussed at the conference well, ranging from uncertainty estimation, via learning hyperparameter tuning, to designing and utilizing geometric priors.
2022/06/21 – RSS feed for new articles and blog-posts
We are happy to unveil a new RSS feed (available at https://www.melba-journal.org/feed.rss), that includes both research articles and blog posts.
2022/05/27 – Recordings of the first MELBA symposium
The recordings of the first MELBA symposium are now available online.