Conclusions and Future Research Directions

Abstract

This chapter presents a conclusion to the work described in this doctoral dissertation. The main contributions are summarized, followed by some suggestions regarding future directions of research related to this work. Concluding RemarksThe main thrust of this thesis is to enable the automatic monitoring of laser-induced changes on tissues during robot-assisted laser microsurgery. Two types of effects were studied: thermal (tissue temperature variation) and mechanical (creation of the incision crater). Surgeon control of these effects is crucial to surgical outcomes, yet these are difficult to perceive and require a significant amount of cognitive acuity. Computer and robot-assisted surgical systems should extend the surgeon performance beyond the limitations of human possibilities, not just in terms of what the surgeon is able to do, but also in the perception of relevant processes that are difficult or impossible to sense. Drawing on these practical problems, this doctoral dissertation focused on the development of models capable of describing the changes induced by surgical lasers on soft tissues, under the condition that these models must be compatible with use in a real surgical setting.This dissertation successfully demonstrates the applicability of statistical learning methods to model the laser incision process during laser microsurgery. To the best of our knowledge, it is the first time that these techniques are applied in this field: analytical models constitute the traditional approach for the analysis of the interaction of the laser with the tissue [1]. With respect to existing approaches, our modeling methodology explicitly considers typical laser parameters used by clinicians during an intervention, (i.e. power, scanning frequency, energy delivery mode, incision length and laser exposure time), thus producing models that are straightforward to use in a surgical scenario either for monitoring or control applications.