Vision based robot assistance in TTTS fetal surgery
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
European Commission's projectSARAS - Smart Autonomous Robotic Assistant Surgeon (EC-H2020-779813)
This paper presents an accurate and robust tracking vision algorithm for Fetoscopic Laser Photo-coagulation (FLP) surgery for Twin-Twin Transfusion Syndrome (TTTS). The aim of the proposed method is to assist surgeons during anastomosis localization, coagulation and review using a tele-operated robotic system. The algorithm computes the relative position of the fetoscope tool tip with respect to the placenta, via local vascular structure registration.The algorithm uses image features (local superficial vascular structures of the placenta’s surface) to automatically match consecutive fetoscopic images. It is composed of three sequential steps: image processing (filtering, binarization and vascular structures segmentation); relevant Points Of Interest (POIs) seletion; and image registration between consecutive images.The algorithm has to deal with the low quality of fetoscopic images, the liquid and dirty environment inside the placenta jointly with the thin diameter of the fetoscope optics and low amount of environment light reduces the image quality. The obtained images are blurred, noisy and with very poor color components.The tracking system has been tested using real video sequences of FLP surgery for TTTS. The computational performance enables real time tracking, locally guiding the robot over the placenta’s surface with enough accuracy.
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CitationSayols, N. [et al.]. Vision based robot assistance in TTTS fetal surgery. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC): proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 5855-5861.
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