End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Intervention

Anh Nguyen, Dennis Kundrat, Giulio Dagnino, Wenqiang Chi, Mohamed E. M. K. Abdelaziz, Yao Guo, YingLiang Ma, Trevor M. Y. Kwok, Celia Riga, Guang-Zhong Yang

Research output: Contribution to conferencePaper

Abstract

Accurate real-time catheter segmentation is an important pre-requisite for robot-assisted endovascular intervention. Most of the existing learning-based methods for catheter segmentation and tracking are only trained on smallscale datasets or synthetic data due to the difficulties of ground-truth annotation. Furthermore, the temporal continuity in intraoperative imaging sequences is not fully utilised. In
this paper, we present FW-Net, an end-to-end and real-time deep learning framework for endovascular intervention. The proposed FW-Net has three modules: a segmentation network with encoder-decoder architecture, a flow network to extract optical flow information, and a novel flow-guided warping function to learn the frame-to-frame temporal continuity. We show that by effectively learning temporal continuity, the network can successfully segment and track the catheters in real-time sequences using only raw ground-truth for training. Detailed validation results confirm that our FW-Net outperforms stateof-
the-art techniques while achieving real-time performance.
Original languageEnglish
Pages(In-press)
Publication statusPublished - 4 Jun 2020
EventInternational Conference on Robotics and Automation - Virtual Conference, Paris, France
Duration: 31 May 20204 Jun 2020
https://www.icra2020.org/

Conference

ConferenceInternational Conference on Robotics and Automation
Abbreviated titleICRA 2020
CountryFrance
CityParis
Period31/05/204/06/20
Internet address

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  • Cite this

    Nguyen, A., Kundrat, D., Dagnino, G., Chi, W., Abdelaziz, M. E. M. K., Guo, Y., ... Yang, G-Z. (2020). End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Intervention. (In-press). Paper presented at International Conference on Robotics and Automation, Paris, France.