Abstract: Systems and methods used to perform touchless registration of images for surgical navigation are disclosed. In some embodiments, the systems include a 3-D scanning device to capture spatial data of a region of interest of a patient and a reference frame. A digital mesh model is generated from the spatial data. A reference frame model is registered with the digital mesh model. Anatomical features of the digital mesh model and a patient registration model are utilized to register the digital mesh model with the patient registration model. A position of a surgical instrument is tracked relative to the reference frame and the patient registration model.

Abstract: Systems and methods used to perform non-contact patient registration of images for surgical navigation are disclosed. In some embodiments, the systems include a 3-D scanning device to capture spatial data of a region of interest of a patient and a reference frame. A digital mesh model is generated from the spatial data. A reference frame model is registered with the digital mesh model. Anatomical features of the digital mesh model and a patient registration model are utilized to register the digital mesh model with the patient registration model. A position of a surgical instrument is tracked relative to the reference frame and the patient registration model.

Abstract: A method and apparatus for performing 2D to 3D registration includes an initialization step and a refinement step. The initialization step is directed to identifying an orientation and a position by knowing orientation information where data images are captured and by identifying centers of relevant bodies. The refinement step uses normalized mutual information and pattern intensity algorithms to register the 2D image to the 3D volume.

Abstract: A method and apparatus for registering physical space to image space is disclosed. The system allows for determining fiducial markers as pixels or voxels in image data. The system can correlate and register the determined fiducial points with fiducial markers in physical space.

Abstract: A method and apparatus for performing 2D to 3D registration includes an initialization step and a refinement step. The initialization step is directed to identifying an orientation and a position by knowing orientation information where data images are captured and by identifying centers of relevant bodies. The refinement step uses normalized mutual information and pattern intensity algorithms to register the 2D image to the 3D volume.

Abstract: A method and apparatus for performing 2D to 3D registration includes an initialization step and a refinement step. The initialization step is directed to identifying an orientation and a position by knowing orientation information where data images are captured and by identifying centers of relevant bodies. The refinement step uses normalized mutual information and pattern intensity algorithms to register the 2D image to the 3D volume.

Abstract: A method and apparatus for performing 2D to 3D registration includes an initialization step and a refinement step. The initialization step is directed to identifying an orientation and a position by knowing orientation information where data images are captured and by identifying centers of relevant bodies. The refinement step uses normalized mutual information and pattern intensity algorithms to register the 2D image to the 3D volume.

Abstract: A method and apparatus for performing 2D to 3D registration includes an initialization step and a refinement step. The initialization step is directed to identifying an orientation and a position by knowing orientation information where data images are captured and by identifying centers of relevant bodies. The refinement step uses normalized mutual information and pattern intensity algorithms to register the 2D image to the 3D volume.

Abstract: A method and apparatus for performing 2D to 3D registration includes an initialization step and a refinement step. The initialization step is directed to identifying an orientation and a position by knowing orientation information where data images are captured and by identifying centers of relevant bodies. The refinement step uses normalized mutual information and pattern intensity algorithms to register the 2D image to the 3D volume.

Abstract: An image processing arrangement for allowing a number of image processing techniques to be tested on a single sample sheet at a single time. A sample segment of the image may be selected for testing and successively repeated in a sample output for the number of image processing techniques to be tested. The proof page is printed on the printer, with the output of the proof page demonstrating the system operation with the desired image processing technique.