Research Project
6831980
DESCRIPTION (provided by applicant): The speed with which an innovative and improved surgical procedure can be widely adopted is governed principally by the availability of competent surgeon mentors. With its difficult learning curve, minimally invasive surgery has an especially strong need for mentors. Several investigators have developed "telestration," the ability for a remote surgeon mentor to draw on the operating surgeon's video display, to make surgical mentoring available over long distances to increase the availability of mentors. Robotically assisted minimally invasive surgery such as that practiced with the da Vinci surgical robot has the same basic need for mentors, with two special circumstances that amplify the need for mentors: robotically assisted minimally invasive surgery is in its earlier stages, with few qualified mentors, and due to the surgeon's immersion at a control console with a high-fidelity 3D display, a mentor is in a sense "remote" even if he or she is in the same room. Both of these special circumstances make telestration even more attractive for robotically assisted minimally invasive surgery than it is for conventional minimally invasive surgery. The proposed project would meet this challenge by leveraging another aspect of the surgical robot system - the presence of computational power- to apply image correlation algorithms to render 3D telestration drawings from drawings produced in 2D by the mentor. The same image correlation algorithms used to generate the 3D telestration also offer a second major benefit - the ability to virtually "paint" the telestration drawings on the anatomy in the surgeon's 3D view, so that the markings made by the mentor move with the anatomy, appearing to have been made with a paint pen directly on the tissue. In addition to the two immediate benefits of generating 3D telestration and creating drawings that track anatomy, application of these algorithms has broad potential impact in the area of image-guided surgery.
