Cellpose review
Open-source cell and nucleus segmentation with GUI, CLI, and Python workflows.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Cellpose is an open-source Python package and graphical interface for segmenting cells and nuclei in microscopy images. It is aimed at researchers who need image-level segmentation workflows, from using pretrained models to refining them with labeled masks. The project supports 2D and 3D workflows, and its GUI offers image annotation and segmentation alongside command-line and Python API options. It runs locally on Linux, Windows, and macOS, with a hosted Cellpose-SAM demo also available through Hugging Face.
The workflow options are a central strength: Cellpose-SAM and other pretrained models provide a starting point, while fine-tuning can be done through the CLI, notebooks, or training API. That makes the software relevant both to researchers who want a graphical interface and to those building segmentation into Python-based image analysis. GPU acceleration is available through PyTorch with CUDA or Apple MPS. Cellpose is a focused choice for cellular microscopy rather than a general-purpose image editing tool; its described scope centers on cells and nuclei, so teams needing other segmentation tasks should assess whether that focus fits their work.
Cellpose is free and open source under the BSD-3-Clause license, with no paid tiers to weigh against one another. Its desktop, self-hosted, and cloud deployment options accommodate different working environments, while documentation and community channels are the stated support routes. Fine-tuning has a practical prerequisite: labeled masks are needed to train a model. Researchers looking for a free tool with multiple ways to run and customize cell segmentation may find the fit compelling; groups seeking a managed commercial service or support beyond community and documentation should consider alternatives that address those needs.
Cellpose pros and cons
- Where it wins
- Segments cells and nuclei in both 2D and 3D microscopy images
- Offers Cellpose-SAM pretrained models and human-in-the-loop fine-tuning
- Supports GUI, command-line, and Python API workflows
- Where it doesn't
- Fine-tuning requires labeled masks
- The package and programmatic workflows are Python-oriented
- GPU acceleration depends on PyTorch/CUDA or Apple MPS
Cellpose fact sheet, pricing and score →
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. How we rank.
Last updated · How we research and update