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This is our new multi-joint annotation for EndoVis MICCAI Challenge dataset ( https://endovissub-instrument.grand-challenge.org/), which can be used for multi-instrument pose estimation.

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Multi-instrument multi-joint annotation for EndoVis'15 instrument subchallenge dataset

This is our new multi-joint annotation for EndoVis'15 MICCAI Challenge dataset, which can be used for multi-instrument pose estimation.

Citation

If you use the annotation in your research, please use the following BibTeX entry.

@article{du2018articulated,
  title={Articulated multi-instrument 2-D pose estimation using fully convolutional networks},
  author={Du, Xiaofei and Kurmann, Thomas and Chang, Ping-Lin and Allan, Maximilian and Ourselin, Sebastien and Sznitman, Raphael and Kelly, John D and Stoyanov, Danail},
  journal={IEEE transactions on medical imaging},
  volume={37},
  number={5},
  pages={1276--1287},
  year={2018},
  publisher={IEEE}
}

Data

After downloading the EndoVis'15 dataset, the dataset is separated into training (in Tracking_Robotic_Training folder) and test data (in Tracking_Robotic_Testing folder). The training data includes four 45 seconds ex vivo video sequences of interventions, the test set is composed of 15 seconds additional video sequences for each of the training sequence, and two additional 1 minute recorded interventions. The frame resolution is 720 × 576 pixels. Frames examples are shown below:

data_sample

Annotations

Compared to original annotation, our new annotation provides high quality annotation for multiple joints of the instrument. We manually labelled 940 frames of the training data (4479 frames) and 910 frames for the test data (4495 frames). The summery of annotation is listed below:

Label / Frame Summery of the EndoVis Dataset

Seq 1 Seq 2 Seq 3 Seq 4 Seq 5 Seq 6 Total
Train Data 210/1107 240/1125 252/1124 238/1123 940 / 4479
Test Data 80/370 76/375 76/375 76/375 301/1500 301/1500 910/4495

For each instrument, five joints including LeftClasperPoint, RightClasperPoint, HeadPoint, ShaftPoint and EndPoint joint are annotated, and the joint definitions in new annotation are illustrated below:

anno_sample

The tool numbering in the annotation files helps distinguish between the scissor and clasper instrument (illustrated in the first figure). It follows the order below:

  • Tool1: Right Clasper
  • Tool2: Left Clasper
  • Tool3: Right Scissor
  • Tool4: Left Scissor

Contact

If you have any queries, please contact us.

Xiaofei Du: xiaofei.du.13@ucl.ac.uk

License

MIT LICENCE

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This is our new multi-joint annotation for EndoVis MICCAI Challenge dataset ( https://endovissub-instrument.grand-challenge.org/), which can be used for multi-instrument pose estimation.

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