metadata

license: mit
dataset_info:
  features:
    - name: image
      dtype: image
    - name: slide_name
      dtype: string
    - name: x
      dtype: int64
    - name: 'y'
      dtype: int64
    - name: level
      dtype: int64
    - name: patch_size
      sequence: int64
    - name: resize
      sequence: int64
    - name: embedding_vector
      sequence:
        sequence: float64
  splits:
    - name: train
      num_bytes: 4289155572.625
      num_examples: 40115
  download_size: 4289233317
  dataset_size: 4289155572.625
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Dataset Card for Histopathology Dataset

Dataset Summary

This dataset contains 1024x1024 patches of a group of histopathology images taken from the CAMELYON16 dataset and embedding vectors extracted from these patches using the Google Path Foundation model.

Thumbnail of Main Slide

Usage

CAMELYON16: List of images taken from CAMELYON16 dataset:
- test_001.tif
- test_002.tif
- test_003.tif
- test_004.tif
- test_005.tif
- test_006.tif
- test_007.tif
- test_008.tif
- test_009.tif
- test_010.tif
- test_011.tif
- test_012.tif
- test_013.tif
- test_014.tif
- test_015.tif
- test_016.tif
- test_017.tif
- test_018.tif
- test_019.tif
- test_020.tif

Create a folder named wsi and download the images given in the list. Then:

from datasets import load_dataset
import openslide as ops


dataset = load_dataset("Cilem/histopathology-1024")
slide_name = dataset['train'][0]['slide_name']
resize = dataset['train'][0]['resize']
path = os.path.join('wsi', slide_name)
slide = ops.OpenSlide(path)
patch = slide.read_region((x, y), 0, patch_size)
patch = patch.resize(resize)
display(patch)

Supported Tasks

Machine learning applications that can be performed using this dataset:

Classification
Segmentation
Image generation

Languages

English

Dataset Structure

Data Fields

image: Patch image.
slide_name: Main slide name of the patch.
x: X coordinate of the patch.
y: Y coordinate of the patch.
level: Level of the main slide.
patch_size: Size of the patch.
resize: Image size used to obtain embedding vector with Path foundation model.
embedding_vector: Embedding vector of the patch extracted using Path foundation model.

Dataset Creation

Source Data

Original Sources
- CAMELYON16: List of images taken from CAMELYON16 dataset:
  - test_001.tif
  - test_002.tif
  - test_003.tif
  - test_004.tif
  - test_005.tif
  - test_006.tif
  - test_007.tif
  - test_008.tif
  - test_009.tif
  - test_010.tif
  - test_011.tif
  - test_012.tif
  - test_013.tif
  - test_014.tif
  - test_015.tif
  - test_016.tif
  - test_017.tif
  - test_018.tif
  - test_019.tif
  - test_020.tif
- Google Path Foundation: Embedding vectors extracted from the patches using the Path Foundation model.

Considerations for Using the Data

Social Impact and Bias

Attention should be paid to the Path Foundation model licenses provided by Google.