Robust surface tracking combining features, intensity and illumination compensation - Du,X; Clancy,N; Arya,S; Hanna,GB; Kelly,J; Elson,DS; Stoyanov,D (International Journal of Computer Assisted Radiology and Surgery, 2015)
Purpose Recovering tissue deformation during robotic-assisted minimally invasivesurgery (MIS) procedures is important for providing intra-operative guidance,enabling in vivo imaging modalities and enhanced robotic control. The tissue motioncan also be used to apply motion stabilization and to prescribe dynamicconstraints for avoiding critical anatomical structures.Methods Image-based methods based independently on salient features or onimage intensity have limitations when dealing with homogeneous soft-tissues orcomplex reflectance. In this paper, we use a triangular geometric mesh model inorder to combine the advantages of both feature and intensity information andtrack the tissue surface reliably and robustly.Results Synthetic and in vivo experiments are performed to provide quantitativeanalysis of the tracking accuracy of our method, we also show exemplar results forregistering multispectral images where there is only a weak image signal.Conclusions Compared to traditional methods, our hybrid tracking method ismore robust and has improved convergence in the presence of larger displacements,tissue dynamics and illumination changes.