Fully digital microscopes are becoming more and more common in surgical
applications. In addition to high-resolution stereoscopic images of the
operating field, which can be transmitted over long distances or stored
directly, these systems offer further potentials by supporting the
surgical workflow based on their fully digital image processing chain.
For example, the image display can be adapted to the respective surgical
scenario by adaptive color reproduction optimization or image overlays
with additional information, such as the tissue topology. Knowledge of
this topology can be used for computer-assisted or AR-guided
microsurgical treatments and enables additional features such as
spatially resolved spectral reconstruction of surface reflectance. In
this work, a new method for high-resolution depth measurements in
digital microsurgical applications is proposed, which is based on the
principle of laser triangulation. Part of this method is a sensor data
fusion procedure to properly match the laser scanner and camera data. In
this context, a strategy based on RBF interpolation techniques is
presented to handle missing or corrupt data, which, due to the measuring
principle, can occur on steep edges and through occlusion. The proposed
method is used for the acquisition of high-resolution depth profiles of
various organic tissue samples, proving the feasibility of the proposed
concept as a supporting technology in a digital microsurgical workflow.