Auto Localization and Segmentation of Occluded Vessels in Robot-Assisted Partial Nephrectomy

  • Alborz Amir-Khalili
  • Jean-Marc Peyrat
  • Julien Abinahed
  • Osama Al-Alao
  • Abdulla Al-Ansari
  • Ghassan Hamarneh
  • Rafeef Abugharbieh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

Abstract

Hilar dissection is an important and delicate stage in partial nephrectomy during which surgeons remove connective tissue surrounding renal vasculature. Potentially serious complications arise when vessels occluded by fat are missed in the endoscopic view and are not appropriately clamped. To aid in vessel discovery, we propose an automatic method to localize and label occluded vasculature. Our segmentation technique is adapted from phase-based video magnification, in which we measure subtle motion from periodic changes in local phase information albeit for labeling rather than magnification. We measure local phase through spatial decomposition of each frame of the endoscopic video using complex wavelet pairs. We then assign segmentation labels based on identifying responses of regions exhibiting temporal local phase changes matching the heart rate frequency. Our method is evaluated with a retrospective study of eight real robot-assisted partial nephrectomies demonstrating utility for surgical guidance that could potentially reduce operation times and complication rates.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Alborz Amir-Khalili
    • 1
  • Jean-Marc Peyrat
    • 2
  • Julien Abinahed
    • 2
  • Osama Al-Alao
    • 3
  • Abdulla Al-Ansari
    • 2
    • 3
  • Ghassan Hamarneh
    • 4
  • Rafeef Abugharbieh
    • 1
  1. 1.BiSICLUniversity of British ColumbiaVancouverCanada
  2. 2.Qatar Robotic Surgery CentreQatar Science & Technology ParkDohaQatar
  3. 3.Urology DepartmentHamad General Hospital, Hamad Medical CorporationQatar
  4. 4.Medical Image Analysis LabSimon Fraser UniversityBurnabyCanada

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