This thesis lays the groundwork for the automaticsupervision of the laser incision process, which aims to complement surgeonsperception of the state of tissues and enhance their control over laserincisions. The research problem is formulated as the estimation of variablesthat are representative of the state of tissues during laser cutting. Priorresearch in this area leveraged numerical computation methods that bear a highcomputational cost and are not straightforward to use in a surgical setting.This book proposes a novel solution to this problem, using models inspired bythe ability of experienced surgeons to perform precise and clean laser cutting.It shows that these new models, which were extracted from experimental datausing statistical learning techniques, are straightforward to use in a surgicalsetup, 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 automaticsupervision of the laser incision process, which aims to complement surgeonsperception of the state of tissues and enhance their control over laserincisions. The research problem is formulated as the estimation of variablesthat are representative of the state of tissues during laser cutting. Priorresearch in this area leveraged numerical computation methods that bear a highcomputational cost and are not straightforward to use in a surgical setting.This book proposes a novel solution to this problem, using models inspired bythe ability of experienced surgeons to perform precise and clean laser cutting.Ilc9