Segmentation-based registration of organs in intraoperative video sequences

  • Authors:
  • James Goddard;Timothy Gee;Hengliang Wang;Alexander M. Gorbach

  • Affiliations:
  • Image Science and Machine Vision Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee;Image Science and Machine Vision Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee;Naval Medical Research Center, Silver Spring, Maryland;National Institutes of Health, Bethesda, Maryland

  • Venue:
  • ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
  • Year:
  • 2006

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Abstract

Intraoperative optical imaging of exposed organs in visible, near-infrared, and infrared (IR) wavelengths in the body has the potential to be useful for real-time assessment of organ viability and image guidance during surgical intervention. However, the motion of the internal organs presents significant challenges for fast analysis of recorded 2D video sequences. The movement observed during surgery, due to respiration, cardiac motion, blood flow, and mechanical shift accompanying the surgical intervention, causes organ reflection in the image sequence, making optical measurements for further analysis challenging. Correcting alignment is difficult in that the motion is not uniform over the image. This paper describes a Canny edge-based method for segmentation of the specific organ or region under study, along with a moment-based registration method for the segmented region. Experimental results are provided for a set of intraoperative IR image sequences.