5 papers
Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift
Joshua Talks, Kevin Marchesini, Luca Lumetti +2
Model reuse offers a solution to the challenges of segmentation in biomedical imaging, where high data annotation costs remain a major bottleneck for deep learning. However, althou…
IConE: Batch Independent Collapse Prevention for Self-Supervised Representation Learning
Konstantinos Almpanakis, Anna Kreshuk
Self-supervised learning (SSL) has revolutionized representation learning, with Joint-Embedding Architectures (JEAs) emerging as an effective approach for capturing semantic featur…
MIFA: Metadata, Incentives, Formats, and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis
Teresa Zulueta-Coarasa, Florian Jug, Aastha Mathur +24
Artificial Intelligence methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new methods, but a…
Tiling artifacts and trade-offs of feature normalization in the segmentation of large biological images
Elena Buglakova, Anwai Archit, Edoardo D'Imprima +3
Segmentation of very large images is a common problem in microscopy, medical imaging or remote sensing. The problem is usually addressed by sliding window inference, which can theo…
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities
Charlotte Bunne, Yusuf Roohani, Yanay Rosen +39
The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determ…