Abstract
In this paper we present an augmented reality system for laparoscopic cholecystectomy video sequences enhancing. Augmented reality allows surgeons to view, in transparency, occluded anatomical and pathological structures constructed preoperatively using medical images such as MRI or CT-Scan. The deformable nature of digestive organs leads to a high dimensionality N-degrees of freedom detection and tracking problem. We describe a knowledge-based construction method of powerful statistical color models for anatomical structures and surgical instruments classification. Thanks to a new wavelet based multi-resolution analysis of the virtual reality models and the anatomical color space; we can detect and track digestive organs to ensure marker less laparoscopic monocular camera pose and preoperative 3D model registration. Results are shown on both synthetic and real data.