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IMSAD: ImPACT Micro-Surgical Anastomose Database

Introduction

The ImPACT Micro-Surgical Anastomose Database (IMSAD) is composed of 23 sessions of robotic micro-surgical anastomose on 0.7 mm artificial blood vessel. These sessions were realized by 5 participants, with different levels of expertise, using a master-slave robotic platform. The data was collected through a collaboration between the MediCIS team of the LTSI (France), and the department of mechanical engineering at the University of Tokyo (Japan) website. The release of this database has been approved by all collaborators.

For each session of IMSAD the following synchronized data are available:

  • Video data: stereoscopic video, 960×540 px, 30 Hz;
  • Kinematic data: 2 robotic arms, position and rotation, 30 Hz;
  • Procedural description: multi-granularity (phases, steps, and activities), both robotic arms.
  • Needle localization: bounding box estimation, left video side, limited to suture phase, 30 hz
  • Scene segmentation data: Manual surgical tools and vessel segmentation, left video side, 1/8 Hz

Downloads

The IMSAD dataset could be downloaded here (only one image to test)

Citation

If you use this dataset, please cite the following paper(s):

  • to be determined/written

Publication using the IMSAD data set

<bibtex> @article{Huaulme2018Sequentialsurgicalsignatures,

author = {Huaulmé, A. and Harada, K. and Forestier, G.. and Mitsuishi, M. and Jannin, P.},
title = {Sequential surgical signatures in micro-suturing task},
journal = {International Journal of Computer Assisted Radiology and Surgery},
year = {2018},
volume = {13},
number = {9},
pages = {1419--1428},
url = {https://doi.org/10.1007/s11548-018-1775-x}

}

@article{Forestier2018Surgicalmotionanalysis,

author = {Forestier, G. and Petitjean, F. and Senin, P. and Despinoy, F. and Huaulmé, A. and Ismail Fawaz, H. and Weber, J. and Idoumghar, L. and Muller, P-A. and Jannin, P.},
title = {Surgical motion analysis using discriminative interpretable patterns},
journal = {Artificial Intelligence in Medicine},
year = {2018},
volume = {81},
pages = {3--11},
url = {https://doi.org/10.1016/j.artmed.2018.08.002}

}

@article{Nakasawa2019,

author = {Nakasawa, A. and Harada, K. and Mitsuishi, M. and Jannin P.},
title = {Real-time surgical needle detection using region-based convolutional neural networks},
journal = {Computer Assisted Radiology and Surgery Conference (CARS)},
year = {2019},
volume = {},
pages = {},

} </bibtex>

Acknowledgements

This work as part of the Bionic Humanoids Propelling New Industrial Revolution program, and was funded by ImPACT Program of Council for Science, Technology and Innovation, Cabinet Office, Government of Japan. It was website . Video

Authors thanks the IRT b\textless \textgreater com for the provision of the software ``Surgery Workflow Toolbox [annotated]'' , used to created procedural description. website

Contacts

inserm rennes1 ltsi