scientific-skills/histolab/references/slide_management.md
The Slide class is the primary interface for working with whole slide images (WSI) in histolab. It provides methods to load, inspect, and process large histopathology images stored in various formats.
from histolab.slide import Slide
# Initialize a slide with a WSI file and output directory
slide = Slide(processed_path="path/to/processed/output",
slide_path="path/to/slide.svs")
Parameters:
slide_path: Path to the whole slide image file (supports multiple formats: SVS, TIFF, NDPI, etc.)processed_path: Directory where processed outputs (tiles, thumbnails, etc.) will be savedHistolab provides built-in sample datasets from TCGA for testing and demonstration:
from histolab.data import prostate_tissue, ovarian_tissue, breast_tissue, heart_tissue, kidney_tissue
# Load prostate tissue sample
prostate_svs, prostate_path = prostate_tissue()
slide = Slide(prostate_path, processed_path="output/")
Available sample datasets:
prostate_tissue(): Prostate tissue sampleovarian_tissue(): Ovarian tissue samplebreast_tissue(): Breast tissue sampleheart_tissue(): Heart tissue samplekidney_tissue(): Kidney tissue sample# Get slide dimensions at level 0 (highest resolution)
width, height = slide.dimensions
# Get dimensions at specific pyramid level
level_dimensions = slide.level_dimensions
# Returns tuple of (width, height) for each level
# Get base magnification (e.g., 40x, 20x)
base_mag = slide.base_mpp # Microns per pixel at level 0
# Get all available levels
num_levels = slide.levels # Number of pyramid levels
# Access OpenSlide properties dictionary
properties = slide.properties
# Common properties include:
# - slide.properties['openslide.objective-power']: Objective power
# - slide.properties['openslide.mpp-x']: Microns per pixel in X
# - slide.properties['openslide.mpp-y']: Microns per pixel in Y
# - slide.properties['openslide.vendor']: Scanner vendor
# Get thumbnail at specific size
thumbnail = slide.thumbnail
# Save thumbnail to disk
slide.save_thumbnail() # Saves to processed_path
# Get scaled thumbnail
scaled_thumbnail = slide.scaled_image(scale_factor=32)
# Display slide thumbnail with matplotlib
import matplotlib.pyplot as plt
plt.figure(figsize=(10, 10))
plt.imshow(slide.thumbnail)
plt.title(f"Slide: {slide.name}")
plt.axis('off')
plt.show()
# Extract region at specific coordinates and level
region = slide.extract_region(
location=(x, y), # Top-left coordinates at level 0
size=(width, height), # Region size
level=0 # Pyramid level
)
WSI files use a pyramidal structure with multiple resolution levels:
# Check available levels
for level in range(slide.levels):
dims = slide.level_dimensions[level]
downsample = slide.level_downsamples[level]
print(f"Level {level}: {dims}, downsample: {downsample}x")
# Get slide filename without extension
slide_name = slide.name
# Get full path to slide file
slide_path = slide.scaled_image
from histolab.slide import Slide
# Load slide
slide = Slide("slide.svs", processed_path="output/")
# Inspect properties
print(f"Dimensions: {slide.dimensions}")
print(f"Levels: {slide.levels}")
print(f"Magnification: {slide.properties.get('openslide.objective-power', 'N/A')}")
# Save thumbnail for review
slide.save_thumbnail()
import os
from pathlib import Path
slide_dir = Path("slides/")
output_dir = Path("processed/")
for slide_path in slide_dir.glob("*.svs"):
slide = Slide(slide_path, processed_path=output_dir / slide_path.stem)
# Process each slide
print(f"Processing: {slide.name}")