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  ```
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- ## Dataset Details
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- ### Dataset Description
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- <!-- Provide a longer summary of what this dataset is. -->
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- - **Curated by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Language(s) (NLP):** en
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- - **License:** [More Information Needed]
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- ### Dataset Sources [optional]
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- <!-- Provide the basic links for the dataset. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the dataset is intended to be used. -->
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- ### Direct Use
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- <!-- This section describes suitable use cases for the dataset. -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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- [More Information Needed]
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  ## Dataset Structure
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- <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- [More Information Needed]
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- ## Dataset Creation
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- ### Curation Rationale
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- <!-- Motivation for the creation of this dataset. -->
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- [More Information Needed]
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- ### Source Data
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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- #### Data Collection and Processing
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- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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- [More Information Needed]
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- #### Who are the source data producers?
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- <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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- [More Information Needed]
 
 
 
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- ### Annotations [optional]
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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- #### Annotation process
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- <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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- #### Who are the annotators?
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- <!-- This section describes the people or systems who created the annotations. -->
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- #### Personal and Sensitive Information
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- <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
 
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- [More Information Needed]
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- ## More Information [optional]
 
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- [More Information Needed]
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- ## Dataset Card Authors [optional]
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  ## Dataset Card Contact
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- [More Information Needed]
 
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  ```
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+ # ARCADE Combined Dataset (FiftyOne Format)
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+ 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](https://voxel51.com/fiftyone), and includes cleaned segmentation data, metadata fields for clinical context, and embedded visual labels.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Dataset Structure
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+ - `segmentations`: COCO-style detection masks per coronary artery segment.
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+ - `phase`: The acquisition phase of the angiography video.
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+ - `task`: A specific labeling task (segmentation or regression) is used.
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+ - `subset_name`: Subdivision info (train, val, test).
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+ - `coco_id`: Corresponding COCO ID for alignment with original sources.
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+ - `filepath`: Path to the image file.
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+ - `metadata`: Image metadata including dimensions and pixel spacing.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ## Format
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+ This dataset is stored in **FiftyOneDataset format**, which consists of:
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+ - `data.json`: Metadata and label references
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+ - `data/`: Folder containing all image samples
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+ - Optional: auxiliary files (e.g., `README.md`, config, JSON index)
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+ To load it in Python:
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+ ```python
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+ import fiftyone as fo
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+ dataset = fo.Dataset.from_dir(
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+ dataset_dir="arcade_combined_fiftyone",
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+ dataset_type=fo.types.FiftyOneDataset,
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+ )
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+ ```
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+ ## Source
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ The original ARCADE dataset was introduced in the paper:
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+ Labrecque Langlais et al. (2023) Evaluation of Stenoses Using AI Video Models Applied to Coronary Angiographies.
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+ https://doi.org/10.21203/rs.3.rs-3610879/v1
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+ This combined version aggregates and restructures subsets across tasks and phases, harmonized with FiftyOne tooling for streamlined model training and evaluation.
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+ ## License
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+ This dataset is shared for research and academic use only. Please consult the original dataset license for clinical or commercial applications.
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+ ## Citation
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+ ```bibtex
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+ @article{avram2023evaluation,
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+ title={Evaluation of Stenoses Using AI Video Models Applied to Coronary Angiographies},
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+ 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.},
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+ year={2023}
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+ }
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+ ```
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  ## Dataset Card Contact
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+ [Paula Ramos](https://huggingface.co/datasets/pjramg)