Computational and Mathematical Methods in Medicine
Volume 2011 (2011), Article ID 879086, 9 pages
doi:10.1155/2011/879086
Research Article

Visual Measurement of Suture Strain for Robotic Surgery

1Department of Surgery, The University of Chicago, Chicago, IL 60637, USA
2Argonne National Laboratory, Argonne, IL 60439, USA

Received 10 November 2010; Accepted 5 January 2011

Academic Editor: Nestor V. Torres

Copyright © 2011 John Martell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Minimally invasive surgical procedures offer advantages of smaller incisions, decreased hospital length of stay, and rapid postoperative recovery to the patient. Surgical robots improve access and visualization intraoperatively and have expanded the indications for minimally invasive procedures. A limitation of the DaVinci surgical robot is a lack of sensory feedback to the operative surgeon. Experienced robotic surgeons use visual interpretation of tissue and suture deformation as a surrogate for tactile feedback. A difficulty encountered during robotic surgery is maintaining adequate suture tension while tying knots or following a running anastomotic suture. Displaying suture strain in real time has potential to decrease the learning curve and improve the performance and safety of robotic surgical procedures. Conventional strain measurement methods involve installation of complex sensors on the robotic instruments. This paper presents a noninvasive video processing-based method to determine strain in surgical sutures. The method accurately calculates strain in suture by processing video from the existing surgical camera, making implementation uncomplicated. The video analysis method was developed and validated using video of suture strain standards on a servohydraulic testing system. The video-based suture strain algorithm is shown capable of measuring suture strains of 0.2% with subpixel resolution and proven reliability under various conditions.