micro-sam
github.com/computational-cell-analytics/micro-samSegment Anything Model for microscopy: interactive and automatic segmentation of light, electron, and fluorescence microscopy images in 2D and 3D, with domain-specific fine-tuning workflows for scientific imaging (1.5K+ stars)
Sourced from
- Awesome AI for Science — github.com/computational-cell-analytics/micro-sam
- GitHub — github.com/computational-cell-analytics/micro-sam
Related resources
Deep learning-based object detection and segmentation for star-convex shapes, widely adopted for cell and nucleus segmentation in fluorescence and electron microscopy via a compact neural network architecture with non-maximum suppression and shape-based post-processing (Nature Methods 2020, 1.2K+ stars)
Open-source bioimage analysis platform for digital pathology and research, featuring AI-powered cell detection, tissue classification, and whole-slide image analysis with extensible scripting and plugin architecture (1.3K+ stars, actively maintained)
Fast, interactive, multi-dimensional image viewer for Python, foundational platform for scientific imaging AI with a rich plugin ecosystem integrating deep learning segmentation, object tracking, and microscopy analysis workflows (2.6K+ stars)
Generalist deep learning algorithm for cell and nucleus segmentation across diverse image types, with human-in-the-loop training (2.0) and one-click image restoration (3.0), 70K+ training objects (Nature Methods 2021/2022/2025)
Community-driven model zoo and deployment infrastructure for AI-powered bioimage analysis, enabling standardized sharing, validation, and cross-platform execution of deep learning models across Fiji, Ilastik, napari, and other scientific imaging tools (EPFL, EMBL, and global collaborators, actively maintained)
ONNX export of the Cellpose cpsam (Cellpose-SAM) model for cell segmentation in microscopy images.