Wei Ouyang

A conditional latent diffusion transformer predicts immunofluorescence images of 12,800 human proteins from nucleus, ER and microtubule stains, outperforming PUPS and CELL-Diff, including on an unseen drug-treated cell line.

The paper discusses AI4Life's Open Calls and Public Challenges, highlighting the state of bioimage analysis, tool availability, and the need for better data and infrastructure.

BioEngine enables biologists to run, adapt, and deploy bioimage AI models on various hardware by interacting with an AI agent through a user-friendly interface.

The paper analyzes how cell shape correlates with proteomic features across multiple cell lines using image-based spatial proteomics data.

FeatureForest uses foundation model embeddings with random forests to enable fast, accurate segmentation of complex biological images with minimal labeling.

U-FISH improves FISH spot detection accuracy and generalization using a deep learning approach with a U-Net model and a large annotated dataset.

This paper introduces enhancements to deepImageJ, a Fiji/ImageJ plugin, by integrating the Java Deep Learning Library (JDLL) to support multiple deep learning frameworks, enabling complex bioimage analysis tasks.

This paper describes OME-Zarr, a cloud-optimized bioimaging file format developed through community collaboration to improve scalability and data access.

The BioImage Model Zoo provides a community standard, infrastructure, and open repository for sharing, testing, and deploying pre-trained deep learning microscopy models across multiple bioimage analysis tools.

The paper integrates protein imaging and interaction data to create a unified map of eukaryotic cell structure, revealing new subcellular systems and protein associations.

ShareLoc provides an open platform for sharing and reanalyzing SMLM data to enhance image reconstruction through deep learning.

FISH-quant v2 is a modular tool for analyzing smFISH images, enabling detection, segmentation, quantification, and visualization of RNA localization at the single-cell level.