histolab
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Security Assessment
About histolab
Histolab is a specialized Python library designed for the efficient processing of whole slide images (WSI) in digital pathology. It addresses the challenge of handling large gigapixel images by providing automated tissue detection and tile extraction functionalities. This skill simplifies the preparation of datasets for various analytical processes, including deep learning, by ensuring that users can swiftly isolate informative tissue regions from extensive slide data. With its lightweight design, Histolab is particularly suited for straightforward workflows, making it an invaluable tool for researchers and practitioners in the field of pathology.
FAQ
How do I install Histolab?
You can install Histolab using the command: `pip install histolab`.
What file formats does Histolab support?
Histolab supports multiple WSI formats including SVS, TIFF, and NDPI.
Can I create custom tissue masks?
Yes, Histolab allows for custom tissue segmentation and the creation of binary masks.
Is there a limit to the size of the slides I can process?
While Histolab is designed for gigapixel images, performance may vary based on system resources.
Does Histolab require specific Python versions?
The documentation does not specify Python version requirements, but it is advisable to use a recent version of Python for compatibility.
Install histolab
Quick Setup:
- Copy the skill folder to
.claude/skills/ - Claude will automatically detect and use the skill
Repository
K-Dense-AI/claude-scientific-skills