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2018 | OriginalPaper | Chapter

DeepPhase: Surgical Phase Recognition in CATARACTS Videos

Authors : Odysseas Zisimopoulos, Evangello Flouty, Imanol Luengo, Petros Giataganas, Jean Nehme, Andre Chow, Danail Stoyanov

Published in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

Publisher: Springer International Publishing

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Abstract

Automated surgical workflow analysis and understanding can assist surgeons to standardize procedures and enhance post-surgical assessment and indexing, as well as, interventional monitoring. Computer-assisted interventional (CAI) systems based on video can perform workflow estimation through surgical instruments’ recognition while linking them to an ontology of procedural phases. In this work, we adopt a deep learning paradigm to detect surgical instruments in cataract surgery videos which in turn feed a surgical phase inference recurrent network that encodes temporal aspects of phase steps within the phase classification. Our models present comparable to state-of-the-art results for surgical tool detection and phase recognition with accuracies of 99 and 78% respectively.

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previous chapter Automated Performance Assessment in Transoesophageal Echocardiography with Convolutional Neural Networks

next chapter Surgical Activity Recognition in Robot-Assisted Radical Prostatectomy Using Deep Learning

https://endovissub2017-workflow.grand-challenge.org/.

https://cataracts.grand-challenge.org/.

Maier-Hein, L., Vedula, S.S., et al.: Surgical data science for next-generation interventions. Nat. Biomed. Eng. 1(9), 691–696 (2017)CrossRef

Padoy, N., Blum, T., et al.: Statistical modeling and recognition of surgical workflow. Med. Image Anal. 16(3), 632–641 (2012)CrossRef

Meißner, C., Meixensberger, J., et al.: Sensor-based surgical activity recognition in unconstrained environments. Minim. Invasive Ther. Allied Technol. 23(4), 198–205 (2014)CrossRef

Stauder, R., et al.: Random forests for phase detection in surgical workflow analysis. In: Stoyanov, D., Collins, D.L., Sakuma, I., Abolmaesumi, P., Jannin, P. (eds.) IPCAI 2014. LNCS, vol. 8498, pp. 148–157. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07521-1_16CrossRef

Quellec, G., Lamard, M., et al.: Real-time segmentation and recognition of surgical tasks in cataract surgery videos. IEEE Trans. Med. Imaging 33(12), 2352–2360 (2014)CrossRef

Zappella, L., Béjar, B., et al.: Surgical gesture classification from video and kinematic data. Med. Image Anal. 17(7), 732–745 (2013)CrossRef

Du, X., Allan, M., et al.: Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery. Int. J. Comput. Assist. Radiol. Surg. 11(6), 1109–1119 (2016)CrossRef

Bouget, D., Allan, M., et al.: Vision-based and marker-less surgical tool detection and tracking: a review of the literature. Med. Image Anal. 35, 633–654 (2017)CrossRef

He, K., Zhang, X., et al.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2016)

10.

Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2015)

11.

Twinanda, A.P., Shehata, S., et al.: EndoNet: a deep architecture for recognition tasks on laparoscopic videos. IEEE Trans. Med. Imaging 36(1), 86–97 (2017)CrossRef

12.

Zisimopoulos, O., Flouty, E., et al.: Can surgical simulation be used to train detection and classification of neural networks? Healthc. Technol. Lett. 4(5), 216–222 (2017)CrossRef

13.

Stauder, R., Ostler, D., et al.: The TUM LapChole dataset for the M2CAI 2016 workflow challenge. arXiv preprint (2016)

14.

Jin, Y., Dou, Q., et al.: EndoRCN: recurrent convolutional networks for recognition of surgical workflow in cholecystectomy procedure video. IEEE Trans. Med. Imaging (2016)

15.

Trikha, S., Turnbull, A.M.J., et al.: The journey to femtosecond laser-assisted cataract surgery: new beginnings or false dawn? Eye 27(4), 461–473 (2013)CrossRef

16.

Chung, J., Gulcehre, C., et al.: Empirical evaluation of gated recurrent neural networks on sequence modeling (2014)

17.

Russakovsky, O., Deng, J., et al.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211–252 (2015)MathSciNetCrossRef

18.

Lea, C., Vidal, R., Reiter, A., Hager, G.D.: Temporal convolutional networks: a unified approach to action segmentation. In: Hua, G., Jégou, H. (eds.) ECCV 2016. LNCS, vol. 9915, pp. 47–54. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49409-8_7CrossRef

Title: DeepPhase: Surgical Phase Recognition in CATARACTS Videos
Authors: Odysseas Zisimopoulos
Evangello Flouty
Imanol Luengo
Petros Giataganas
Jean Nehme
Andre Chow
Danail Stoyanov
Publisher: Springer International Publishing
Book: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
Print ISBN: 978-3-030-00936-6

Electronic ISBN: 978-3-030-00937-3

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-00937-3_31

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