Stereovision surface stitching for image updating in open spine surgery

Preoperative CT (pCT) images acquired in a supine position can be inaccurate for intraoperative image guidance in open spine surgery due to alignment change between supine pCT and intraoperative prone positioning. We have developed a level-wise registration framework to compensate for the alignment change using intraoperative stereovision (iSV) data of the exposed spine. A hand-held stereovision system was developed, but the field of view was limited to 1-2 segments per image. Although multiple iSV surfaces can be combined to capture the full field based on tracking information, acquisition is limited to one snapshot at a time with minimized hand motion due to asynchronization between image and tracking data. In this study, we developed methods to concatenate iSV surfaces without relying on tracking information, and illustrate the methods using data acquired from a pig spine. To register two iSV surfaces, the 2D texture maps were registered using an optical flow algorithm, and the 3D point cloud of the second iSV surface was registered with the first using 3D spatial information of each pixel. The two registered iSV surfaces were then merged to form one composite iSV surface. Multiple iSV surfaces were stitched sequentially. Results from 4 image pairs show that 2D and 3D registration accuracy was 2.7±0.6 pixels and 1.0±0.1 mm, respectively, across 8 landmarks. The overall accuracy of the final composite surface was 0.9±0.4 mm. These preliminary data show that iSV can potentially be acquired at video rate to improve efficiency to recover the full surgical field.