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Datasets:
BrachioLab
/
cholecystectomy

Tasks:
Feature Extraction
Image Segmentation
Modalities:
Image
Formats:
parquet
Size:
1K - 10K
Libraries:
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License:
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image
imagewidth (px)
640
640
gonogo
sequencelengths
360
360
organs
sequencelengths
360
360
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Dataset Structure

This dataset contains vision data from cholecystectomy surgery (gallbladder removal).

Data Fields

  • image: The PIL image of the surgery view.
  • gonogo: The (360,640) label of background (0), safe (1), and unsafe (2).
  • organs: The (360,640) label of background (0), liver (1), gallbladder (2), and hepatocystic triangle (3).

Data Splits

  • train: 812 samples
  • test: 203 samples
  • Total: 1015 samples

Usage 

from datasets import load_dataset
train_dataset = load_dataset("BrachioLab/cholecystectomy_segmentation", split="train")
test_dataset = load_dataset("BrachioLab/cholecystectomy_segmentation", split="test")
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
255 MB
Number of rows:
1,015

Models trained or fine-tuned on BrachioLab/cholecystectomy