InitRech 2015/2016, sujet 4
Summary
This scientific document deals with Augmented Reality(AR) for liver surgery. Considerable advances in medicine have seen the development of new surgery techniques, such as MIS (Minimally Invasive Surgery), which give the opportunity for surgeon to reduce several risks. This technique is less invasive as traditional surgery. Indeed, only two or three small incisions are done, and manipulated-instruments are placed through these openings. The main purpose of this technique is to reduce time recovery of the patient but also reducing bleeding, pain and risks of infection. Robotic arms embedded a high resolution stereoscopic camera which give a 3D visual support for surgery.
At this point, stream from stereoscopic vision only gave information about liver's surface. More information is needed to allow manipulated-instruments to navigate in the human's abdominal cavity. Thanks to the improvement of computing, it is now possible to create a digital mapping in real-time of any organ in the human body. The technique consists to modeling an organ (liver for example), with high details (internal structure of the organ), and superimposed digital model with real images from stereoscopic camera. Surgeon can now placed his tools with high accuracy and process data which were invisible or very complex to see before. Research in this kind of work exist for a decade, but previous work deals with static organ and good environments. In reality, organs move (breath, beat heart), have elastic properties and surgery's instruments could create occlusion and smokes. These are really important points and can't be neglected because of the complexity of this kind of surgery.
Several mathematical strategies had been used to create a “digital real-time model”. This model is based on a feature-based tracking algorithm where salient landmarks are detected in each image pair using the SURF descriptor (Speed-Up Robust Features)and are tracked thanks to the Lucas-Kanade optical flow. The biomechanical model is calculated with several parameters as internal forces (deformation), elasticity coefficients because of the vascular structure (which is heterogeneous). In clear, the compute system create points over the liver, tracks in real-time the organ, recalculate his position and estimate deformations. This allow with superimposed to detect defects and localize deformations (as tumors for example). As a result, this create an accurate 3D-real-time-view of the liver and allow surgeons to operate with robotic arms with high efficiency.
