Augmented surgical reality environment

#The present disclosure relates to surgical techniques to improve surgical outcomes for a patient. More specifically, the present disclosure is directed to systems and methods for augmenting and enhancing a clinician's field of vision while performing a surgical technique.

#Minimally invasive surgeries have involved the use of multiple small incisions to perform a surgical procedure instead of one larger opening. The small incisions have reduced patient discomfort and improved recovery times. The small incisions have also limited the visibility of internal organs, tissue, and other matter.

#Endoscopes have been inserted in one or more of the incisions to make it easier for clinicians to see internal organs, tissue, and other matter inside the body during surgery. These endoscopes have included a camera with an optical and/or digital zoom capability that is coupled to a display showing the magnified view of organs, tissue, and matter inside the body as captured by the camera. Existing endoscopes and displays, especially those used in surgical robotic systems, have had a limited ability to identify conditions or objects that are within the field of view of the camera but are not fully visible within the spectrum shown on the display.

#The above and other aspects, features, and advantages of the present disclosure will become more apparent in light of the following detailed description when taken in conjunction with the accompanying drawings in which:

#FIG. 1 is a block diagram of a system for augmenting a surgical environment;

#FIGS. 2A-2D are examples of how the system of FIG. 1 may be implemented;

#Image data captured from a surgical camera during a surgical procedure may be analyzed to identify additional imperceptible properties of objects within the camera field of view that may be invisible or visible but difficult to clearly see for people viewing the camera image displayed on a screen. Various image processing technologies may be applied to this image data to identify different conditions in the patient. For example, Eulerian image amplification techniques may be used to identify wavelength or “color” changes of light in different parts of a capture image. These changes may be further analyzed to identify re-perfusion, arterial flow, and/or vessel types.

#Eulerian image amplification may also be used to make motion or movement between image frames more visible to a clinician. In some instances changes in a measured intensity of predetermined wavelengths of light between different image frames may be presented to a clinician to make the clinician more aware of the motion of particular objects of interest (such as blood).

#Image algebra may be used to identify an optimal location for cutting tissue or other matter during the surgical procedure. In some instances, image algebra may include edge detection and/or Eulerian image amplification to identify optimal cutting locations.