Catálogo de publicaciones - libros

Laser incision of soft tissues is understood as an energy-based, thermal process: the energy associated with the laser beam is absorbed by the tissue under the form of heat, producing a local rise of temperature. Continuous temperature increase eventually breaks molecular bonds and results in the ejection of hot plume. This process is commonly referred to as thermal laser ablation and has been extensively studied in the past, but has never been modeled for monitoring or control purposes. In this thesis, we build models capable of describing the development of laser incisions in soft tissues, given the same inputs used by the clinicians, i.e. the laser operational parameters.

The goal of this chapter is to provide the background that frames the research described in this dissertation. Principles and concepts relevant to the content of subsequent chapters are introduced here. Because this work resides at the intersection of laser-tissue interaction with computer-assisted surgery, the basics of laser technology are introduced here.

This chapter introduces the problem of the automatic supervision of laser-induced effects during laser surgery. A top-down approach is used to tackle this problem: specific circumstances in which surgeons would value enhanced information regarding the effects of their laser actions on tissues are identified. The problem is grounded in the identification of variables of interest that are selected as target for the supervision. In the scope of this thesis, we explore the application of artificial cognitive approaches to monitor these variables in a surgical scenario.

Given the research problem outlined in the previous chapter, here we focus on the development of a methodology to learn the temperature dynamics of tissues subject to thermal laser ablation.

This chapter focuses on the problem of modeling the laser ablation process from a geometrical point of view. The objective is to create a model capable of describing the laser incision depth based on the knowledge of the laser parameters and inputs. The discussion starts with a statement of the problem, which is defined in terms of a supervised regression. Our approach is compared with existing heuristic models for the prediction of ablation depth.

Based on the models presented in Chaps.  and , here we describe the development of a prototypical supervisory system for laser microsurgery.

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.