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kidney | C3L-00096-21.svs | 7,168 | 5,120 | 0 | [
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] |
kidney | C3L-00096-21.svs | 22,016 | 5,120 | 0 | [
512,
512
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224,
224
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kidney | C3L-00096-21.svs | 6,144 | 5,632 | 0 | [
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] |
kidney | C3L-00096-21.svs | 5,120 | 6,656 | 0 | [
512,
512
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224,
224
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kidney | C3L-00096-21.svs | 8,704 | 6,656 | 0 | [
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512
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kidney | C3L-00096-21.svs | 3,072 | 9,216 | 0 | [
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] |
kidney | C3L-00096-21.svs | 12,288 | 10,752 | 0 | [
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512
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224,
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kidney | C3L-00096-21.svs | 6,656 | 11,264 | 0 | [
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] |
kidney | C3L-00096-21.svs | 20,992 | 12,288 | 0 | [
512,
512
] | [
224,
224
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kidney | C3L-00096-21.svs | 7,168 | 12,800 | 0 | [
512,
512
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224,
224
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kidney | C3L-00096-21.svs | 13,824 | 12,800 | 0 | [
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kidney | C3L-00096-21.svs | 20,992 | 12,800 | 0 | [
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512
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kidney | C3L-00096-21.svs | 21,504 | 12,800 | 0 | [
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] |
kidney | C3L-00096-21.svs | 19,456 | 13,312 | 0 | [
512,
512
] | [
224,
224
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kidney | C3L-00096-21.svs | 20,992 | 13,312 | 0 | [
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] |
kidney | C3L-00096-21.svs | 17,920 | 13,824 | 0 | [
512,
512
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224,
224
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kidney | C3L-00096-21.svs | 18,944 | 13,824 | 0 | [
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512
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224,
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kidney | C3L-00096-21.svs | 21,504 | 13,824 | 0 | [
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] |
kidney | C3L-00096-21.svs | 16,896 | 14,336 | 0 | [
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512
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kidney | C3L-00096-21.svs | 17,408 | 14,336 | 0 | [
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] |
kidney | C3L-00096-21.svs | 17,920 | 14,336 | 0 | [
512,
512
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kidney | C3L-00096-21.svs | 18,432 | 14,336 | 0 | [
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512
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224,
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kidney | C3L-00096-21.svs | 18,944 | 14,336 | 0 | [
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kidney | C3L-00096-21.svs | 8,704 | 14,848 | 0 | [
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512
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Dataset Card for Mixed Histopathology Dataset
Dataset Summary
This dataset contains 512x512 patches of a group of histopathology images taken from the CAMELYON16 , CANCER IMAGING ARCHIVE-KIDNEY, CANCER IMAGING ARCHIVE-COLON, CANCER IMAGING ARCHIVE-LUNG datasets 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.tiftest_002.tiftest_003.tiftest_004.tiftest_005.tiftest_006.tiftest_007.tiftest_008.tiftest_009.tiftest_010.tif
CANCER IMAGING ARCHIVE-KIDNEY: List of images taken from CANCER IMAGING ARCHIVE-KIDNEY dataset:
C3L-00004-21.svsC3L-00004-26.svsC3L-00010-21.svsC3L-00010-26.svsC3L-00011-21.svsC3L-00011-26.svsC3L-00026-21.svsC3L-00026-26.svsC3L-00079-21.svsC3L-00079-26.svs
CANCER IMAGING ARCHIVE-COLON: List of images taken from CANCER IMAGING ARCHIVE-COLON dataset:
MSB-00241-01-05.svsMSB-00241-01-06.svsMSB-00352-03-05.svsMSB-00352-03-10.svsMSB-00352-05-02.svsMSB-00643-03-06.svsMSB-00643-03-11.svsMSB-00643-03-12.svsMSB-00643-03-13.svsMSB-00952-01-02.svs
CANCER IMAGING ARCHIVE-LUNG: List of images taken from CANCER IMAGING ARCHIVE-LUNG dataset:
C3L-00001-21.svsC3L-00001-26.svsC3L-00009-21.svsC3L-00009-26.svsC3L-00080-21.svsC3L-00080-26.svsC3L-00083-21.svsC3L-00083-26.svsC3L-00093-21.svsC3L-00093-26.svs
- The slide list given above can be found under the wsis folder.
from datasets import load_dataset
import openslide as ops
dataset = load_dataset("Cilem/histopathology-1024")
slide_name = dataset['train'][0]['slide_name']
organ = dataset['train'][0]['organ']
resize = dataset['train'][0]['resize']
path = os.path.join('wsis', organ, 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
organ: Organ name of the patch.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
- CANCER IMAGING ARCHIVE-KIDNEY
- CANCER IMAGING ARCHIVE-COLON
- CANCER IMAGING ARCHIVE-LUNG
- 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.
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