Real time tracking of exterior and interior organ surfaces using sparse sampling of the exterior surfaces
This paper presents a new algorithm for real time tracking of the exterior and interior surfaces of organs using sparse sampling of the exterior surfaces. The tracking is based on identifying subspaces in which the coefficients of spherical harmonic representations of the surfaces live. It uses pre operative CT/MRI scans during training, and needlescopic images acquired during tracking. We study different strategies for sampling the exterior organ surface using the needlescopic images and also apply the method to 3D frame interpolation. Specially, we provide (1)the first demonstration of real time interior organ surface reconstruction using sparse sampling of exterior surfaces with error rate as low as 0.095%, and (2) algorithms' application in 3D cardiac frame interpolation with error rate of only 1.15%while reducing radiation rate by 90%.