All Competitors

Channel-adaptive autoregressive generative model that synthesizes in-silico fluorescence microscopy of protein subcellular localization from amino-acid sequence and cellular landmark stains.

A DINO-pretrained vision transformer for accurate, robust segmentation of micronuclei in DNA-stained fluorescence microscopy across cell lines and instruments.

A NAFNet backbone trained with a perceptual GAN objective for high-fidelity bioimage restoration, achieving best LPIPS on 7 of 8 AI4Life benchmarks.

An all-in-one foundation model for microscopic image restoration, unifying 8 tasks across 5 microscopy modalities and 2D/3D data, with zero-shot inference on unseen imaging systems.

Flow-matching generative model that simulates high-resolution fluorescence images of human fibroblasts conditioned on surface micro-topographies, a digital twin of cell-material interactions.

A differentiable wave-optical framework for label-agnostic computational microscopy of biomolecular density and orientation across diverse imaging modalities.

Self-supervised Vision Transformer models trained on proteome-wide fluorescence microscopy images from the Human Protein Atlas for subcellular protein localization.

Foundation model for fluorescence microscopy image restoration, unifying super-resolution, denoising, isotropic reconstruction, projection, and volumetric reconstruction in one Swin transformer.

Human-in-the-loop cell segmentation framework enabling custom model training from as few as 100-200 corrected annotations.

Generalist deep learning algorithm for cell and nucleus instance segmentation using simulated diffusion flows, without per-dataset retraining.