MOSXAV: A Benchmark Dataset for Multi-Object Segmentation in X-ray Angiography Videos

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1. Overview

MOSXAV is a benchmark dataset designed for multi-object segmentation in X-ray angiography videos. It provides high-quality, manually annotated segmentation ground truth, supporting the analysis of vascular structures in dynamic medical imaging. Each video contains 33$\sim$70 frames at a resolution of 512$\times$512 pixels. Vascular regions are annotated by experienced radiologists, with annotations focused on one or two key frames where the contrast agent is most prominent.

• The training and validation sets include 50 sequences (2,335 frames), with annotations every 5 frames.
• The test set consists of 12 sequences (488 frames), with frame-level annotations throughout.

MOSXAV provides a valuable resource for the development and benchmarking of methods in X-ray angiography video segmentation.

File Structure

2. Download

[GoogleDrive] [OneDrive] [BaiduPan]

3. License

The dataset is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. See LICENSE for details.

Citation

Please consider to cite MOSXAV if it helps your research.

@inproceedings{MOSE,
  title={{MOSE}: A New Dataset for Video Object Segmentation in Complex Scenes},
  author={Ding, Henghui and Liu, Chang and He, Shuting and Jiang, Xudong and Torr, Philip HS and Bai, Song},
  booktitle={ICCV},
  year={2023}
}