
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

Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection
2022/04/27
Haleh AkramiUniversity of Southern California, Anand JoshiUniversity of Southern California, Sergul AydoreAmazon Web Services, Richard LeahyUniversity of Southern California
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2022/03/19 – First MELBA Symposium
Mark your calendars! We will have the first virtual MELBA Symposium on May 5, 2022, between 9a-11a US EDT.
Two papers, selected by a readers’ vote, will be presented and discussed in detail:
- Raumanns, R., Schouten, G., Joosten, M., Pluim, J. P., & Cheplygina, V. ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification;
- Quiros, A. C., Murray-Smith, R., & Yuan, K. PathologyGAN: Learning deep representations of cancer tissue.
2022/02/17 – Announcing the MELBA Symposium Initiative
The MELBA Journal is excited to announce a new initiative that aims to increase engagement between authors and readers, and spotlight high quality papers.
We plan to have an online (virtual) symposium, multiple times a year, where two or three papers that were previously published in MELBA, will be presented by the authors and interactively discussed in detail.
2021/10/22 – New website!
We are excited and proud to unveil the new Melba website, which will take the place of the old Scholastica one.