Facial landmark‐guided surface matching for image‐to‐patient registration with an RGB‐D camera

xlomafota13 shared this article with you from Inoreader Facial landmark‐guided surface matching for image‐to‐patient registration with an RGB‐D camera Via The International Journal of Medical Robotics and Computer Assisted Surgery Abstract Background Fiducial marker-based image-to-patient registration is the most common way in image-guided neurosurgery, which is labour-intensive, time consuming, invasive and error prone. Methods We proposed a method of facial landmark-guided surface matching for image-to-patient registration using an RGB-D camera. Five facial landmarks are localised from preoperative magnetic resonance (MR) images using deep learning and RGB image using Adaboost with multi-scale block local binary patterns, respectively. The registration of two facial surface point clouds derived from MR images and RGB-D data is initialised by aligning these five landmarks and further refined by weighted iterative closest point algorithm. Results Phantom experiment results show the target registration error is less than 3 mm when the distance from the camera to the phantom is less than 1000 mm. The registration takes less than 10 s. Conclusions The proposed method is comparable to the state-of-the-arts in terms of the accuracy yet more time-saving and non-invasive. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.