This thesis lays the groundwork for the automatic
supervision of the laser incision process, which aims to complement surgeons’
perception of the state of tissues and enhance their control over laser
incisions. The research problem is formulated as the estimation of variables
that are representative of the state of tissues during laser cutting. Prior
research in this area leveraged numerical computation methods that bear a high
computational cost and are not straightforward to use in a surgical setting.
This book proposes a novel solution to this problem, using models inspired by
the ability of experienced surgeons to perform precise and clean laser cutting.
It shows that these new models, which were extracted from experimental data
using statistical learning techniques, are straightforward to use in a surgical
setup, allowing greater precision in laser-based surgical procedures.
Introduction.- Background: Laser Technology and Applications to Clinical Surgery.- Cognitive Supervision for Transoral Laser Microsurgery .- Learning the Temperature Dynamics During Thermal Laser Ablation.- Modeling the Laser Ablation Process.- Realization of a Cognitive Supervisory System for Laser Microsurgery.- Conclusions and Future Research Directions.
This thesis lays the groundwork for the automatic
supervision of the laser incision process, which aims to complement surgeons’
perception of the state of tissues and enhance their control over laser
incisions. The research problem is formulated as the estimation of variables
that are representative of the state of tissues during laser cutting. Prior
research in this area leveraged numerical computation methods that bear a high
computational cost and are not straightforward to use in a surgical setting.
This book proposes a novel solution to this problem, using models inspired by
the ability of experienced surgeons to perform precise and clean laser cutting.
It shows that these new models, which were extracted from experimental data
using statistical learning techniques, are straightforward to use in a surgical
setup, allowing greater precision in laser-based surgical procedures.
Nominated
as an outstanding PhD thesis by the University of
Genoa, Italy
Presents
innovative research on the automatic supervision of laser incision process
Proposes
novel solutions for achieving precise and clean laser cutting in a surgical
setting
Describes
a new methodology for modeling laser-induced effects on tissue
