microscopy

Today in AI for life science: an AI agent that drives ImageJ, the case for ’thinking microscopes’ that run their own experiments, and a foundation model that imagines how cells morph under perturbation.

Control microscopes in plain language — LLM agents that turn scientific intent into imaging, segmentation, and analysis.

A collaborative community roadmap surveying how deep learning is applied across microscopy — image restoration, detection, segmentation, classification, tracking, and multimodal fusion — with its possibilities and limitations.

A framework that makes deep-learning pipelines for microscopy flexible, shareable, and reproducible across computing environments.

Building an AI-powered self-driving microscopy system for studying cellular response