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Dataset Card for btcv
This is a FiftyOne dataset with 30 video 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("Voxel51/BTCV-CT-as-video-MedSAM2-dataset")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details
Dataset Description
This dataset is the "Beyond the Cranial Vault" (BTCV) dataset used by Medical-SAM2 paper. Med-SAM2 fine-tunes the Segment Anything Model 2 on to accurately segment CT-scan imagery.
The paper "adopts the philosophy of taking medical images as videos"; so, the images have been converted into videos, and maybe easily resampled into frames using dataset.to_frames(sample_frames=True)
.
- Curated by: Synapse
- Shared by [optional]: Jiayuan Zhu and Med-SAM2 Authors
Dataset Sources [optional]
- Med-SAM2 Github Repository: MedicineToken/Medical-SAM2
- Paper: Medical SAM 2: Segment medical images as video via Segment Anything Model 2
- Data Repository: Med-SAM2 preprocessed dataset on HF
- Demo [optional]: [Coming Soon...]
Uses
Direct Use
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Dataset Structure
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Dataset Creation
Curation Rationale
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Source Data
Data Collection and Processing
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Who are the source data producers?
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Annotations [optional]
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Bias, Risks, and Limitations
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Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
Citation [optional]
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Glossary [optional]
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