Dataset Card for arcade_combined_export

This is a FiftyOne dataset with 3000 samples.

Installation

If you haven't already, install FiftyOne:

pip install -U fiftyone

Usage

import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("pjramg/arcade_fiftyone")

# Launch the App
session = fo.launch_app(dataset)

ARCADE Combined Dataset (FiftyOne Format)

The ARCADE Combined Dataset is a curated collection of coronary angiography images and annotations designed to evaluate coronary artery stenosis. This version has been processed and exported using FiftyOne, and includes cleaned segmentation data, metadata fields for clinical context, and embedded visual labels.

Dataset Structure

segmentations: COCO-style detection masks per coronary artery segment.
phase: The acquisition phase of the angiography video.
task: A specific labeling task (segmentation or regression) is used.
subset_name: Subdivision info (train, val, test).
coco_id: Corresponding COCO ID for alignment with original sources.
filepath: Path to the image file.
metadata: Image metadata including dimensions and pixel spacing.

Format

This dataset is stored in FiftyOneDataset format, which consists of:

data.json: Metadata and label references
data/: Folder containing all image samples
Optional: auxiliary files (e.g., README.md, config, JSON index)

To load it in Python:

import fiftyone as fo
dataset = fo.Dataset.from_dir(
    dataset_dir="arcade_combined_fiftyone",
    dataset_type=fo.types.FiftyOneDataset,
)

Source

The original ARCADE dataset was introduced in the paper:

Labrecque Langlais et al. (2023) — Evaluation of Stenoses Using AI Video Models Applied to Coronary Angiographies. https://doi.org/10.21203/rs.3.rs-3610879/v1

This combined version aggregates and restructures subsets across tasks and phases, harmonized with FiftyOne tooling for streamlined model training and evaluation.

License

This dataset is shared for research and academic use only. Please consult the original dataset license for clinical or commercial applications.

Citation

@article{avram2023evaluation,
  title={Evaluation of Stenoses Using AI Video Models Applied to Coronary Angiographies},
  author={Labrecque Langlais, E. and Corbin, D. and Tastet, O. and Hayek, A. and Doolub, G. and Mrad, S. and Tardif, J.-C. and Tanguay, J.-F. and Marquis-Gravel, G. and Tison, G. and Kadoury, S. and Le, W. and Gallo, R. and Lesage, F. and Avram, R.},
  year={2023}
}

Dataset Card Contact

Paula Ramos

image imagewidth (px) 512 512