Histolab WSI Processing

Histolab WSI Processing

Overview

Histolab is a Python library for processing whole slide images (WSI) in digital pathology. It automates tissue detection, extracts informative tiles from gigapixel images using multiple strategies, and provides composable filter pipelines for preprocessing. The library handles SVS, TIFF, NDPI, and other WSI formats via OpenSlide.

When to Use

• Extracting tiles from whole slide images for deep learning model training
• Detecting tissue regions and filtering background/artifacts in histopathology slides
• Building preprocessing pipelines for H&E or IHC stained tissue sections
• Creating quality-driven tile datasets ranked by nuclei density or cellularity
• Performing batch tile extraction across slide collections with consistent parameters
• Assessing slide quality and tissue coverage before computational pathology workflows
• For raw slide access without tile extraction, use openslide-python directly
• For complex multiplexed imaging or spatial proteomics pipelines, use pathml instead

Prerequisites

• Python packages: histolab (includes OpenSlide Python bindings)
• System dependency: OpenSlide C library must be installed separately
• Supported formats: SVS, TIFF, NDPI, VMS, SCN, MRXS (via OpenSlide)

# macOS
brew install openslide
pip install histolab

# Ubuntu/Debian
sudo apt-get install openslide-tools
pip install histolab

Quick Start

from histolab.slide import Slide
from histolab.tiler import RandomTiler

# Load slide