Virtual reality and augmented reality applied to laparoscopic and notes procedures

Computer-assisted surgery led to a major improvement in medicine. Such an improvement can be summarized in three major steps. The first one consists in an automated 3D modelling of patients from their medical images. The second one consists in using this modelling in surgical planning and simulator software offering then the opportunity to train the surgical gesture before carrying it out. The last step consists in intraoperatively superimposing preoperative data onto the real view of patients. This augmented reality provides surgeons a view in transparency of their patient allowing to track instruments and improve pathology targeting. We will present here our results in these different domains applied to laparoscopic and NOTES procedures.

[1]  H. Peitgen,et al.  Computer-Assisted Operative Planning in Adult Living Donor Liver Transplantation: A New Way to Resolve the Dilemma of the Middle Hepatic Vein , 2005, World Journal of Surgery.

[2]  J. Marescaux,et al.  Three-Dimensional Virtual Cholangioscopy: A Reliable Tool for the Diagnosis of Common Bile Duct Stones , 2004, Annals of surgery.

[3]  Luc Soler,et al.  Evaluation of a New 3D/2D Registration Criterion for Liver Radio-Frequencies Guided by Augmented Reality , 2003, IS4TH.

[4]  Yo-Sung Ho,et al.  Automatic liver segmentation for volume measurement in CT Images , 2006, J. Vis. Commun. Image Represent..

[5]  Isabelle Bloch,et al.  Computational modeling of thoracic and abdominal anatomy using spatial relationships for image segmentation , 2004, Real Time Imaging.

[6]  Johan Montagnat,et al.  Fully Automatic Anatomical, Pathological, and Functional Segmentation from CT Scans for Hepatic Surgery , 2000, Medical Imaging: Image Processing.

[7]  Luc Soler,et al.  A low cost and accurate guidance system for laparoscopic surgery: validation on an abdominal phantom , 2005, VRST '05.

[8]  J. Marescaux,et al.  Augmented-reality-assisted laparoscopic adrenalectomy. , 2004, JAMA.

[9]  Jean-Baptiste Fasquel,et al.  A modular and evolutive component oriented software architecture for patient modeling , 2006, Comput. Methods Programs Biomed..

[10]  Luc Soler,et al.  Computer-assisted operative procedure: from preoperative planning to simulation , 2006 .

[11]  Alexandre Hostettler,et al.  Real-time ultrasonography simulator based on 3D CT-scan images. , 2005, Studies in health technology and informatics.

[12]  Jong-Won Park,et al.  Automatic Segmentation Technique Without User Modification for 3D Visualization in Medical Images , 2004, CIS.

[13]  Hans-Peter Meinzer,et al.  A Statistical Deformable Model for the Segmentation of Liver CT Volumes , 2007 .

[14]  Doron Levy,et al.  Registration-based morphing of active contours for segmentation of ct scans. , 2004, Mathematical biosciences and engineering : MBE.

[15]  Alexandre Hostettler,et al.  Real Time Simulation of Organ Motions Induced by Breathing: First Evaluation on Patient Data , 2006, ISBMS.

[16]  Luc Soler,et al.  PACS-based interface for 3D anatomical structure visualization and surgical planning , 2002, SPIE Medical Imaging.

[17]  Marco Nolden,et al.  COMPUTER-BASED SURGERY PLANNING FOR LIVING LIVER DONATION , 2004 .

[18]  Outi Sipilä,et al.  Preoperative hepatic 3D models: virtual liver resection using three-dimensional imaging technique. , 2005, European journal of radiology.

[19]  Heinz-Otto Peitgen,et al.  Efficient Semiautomatic Segmentation of 3D Objects in Medical Images , 2000, MICCAI.

[20]  Stephane Cotin,et al.  EP4A: Software and Computer Based Simulator Research: Development and Outlook SOFA—An Open Source Framework for Medical Simulation , 2007, MMVR.