| dc.description.abstract | Comparing with conventional brain surgery, minimally invasive endoscopic surgery has the advantages of small wounds, rapid recovery of patients after surgery, and less damage to brain tissues. Therefore, minimally invasive endoscopic surgery has been booming in the past decade. When surgeons perform the minimally invasive brain endoscopic surgery, they can only use the endoscopic and CT/MRI images with their own anatomic knowledge and clinical experience to guess the existence of brain vessels or nerves behind the endoscopic image. Therefore, the surgeons need to be very careful intraoperatively to avoid damaging cerebral arteries or nerves, causing cerebral edema and intracranial hemorrhage.
This research develops an endoscopic surgical navigation system, by modifying the path planning method and integrating the AR system into the existing CT image based navigation system to provide an easy and intuitive way for planning a safe surgical path that can avoid important brain tissues such as cerebral arteries and nerves. This research also adds new path planning functions and virtual endoscopic images of arteries onto the current endoscopic image so that the surgeons realize the existence of arteries behind the current endoscopic image.
Two experiments of this research can were completed. The first experiment is to measure the accuracy of camera calibration, and the results show that the average distance error of feature points is0.75±0.49pixel. The second experiment is to measure the accuracy of hand-eye calibration. The results show that the average distance error is 0.41±0.13mm. Under the good condition of the accuracy of the navigation system, then the result of this experiment is lower than the clinical requirement range (2mm). | en_US |