• robotic surgery
• automation
• medical robotics
• focused ultrasound
• non.invasive
• optimization

Focused ultrasound (FUS) is a non-invasive therapeutic technology that could revolutionize the treatment paradigm of various medical conditions. It allows to produce a localized effect that can destroy tissue without requiring any incision nor ionizing radiation. Despite these ideal advantages offered by FUS, the currently available platforms feature some limitations that still restrict its actual employment in surgery. This Thesis focuses on the use of Robotics as the enabling technology for the automated planning and execution of a FUS thermal treatment, attempting to address these limitations while striving for the optimization of relevant characteristics of the treatment itself.

The proposed method is divided into two modules. The first one concerns the reconstruction of a 3D image of the volume to be treated from diagnostic ultrasound images, taking advantage of robot assistance and the introduction of a deep learning algorithm. The second presents the planning of an optimized strategy for the safe and complete ablation of a volume that has been previously mapped. Validation was carried out both through experimental tests and with simulation software. The result of this work is a successful proof of concept which integrates the two modules. Further work may be useful for clinical translation in improving human-robot interaction during the procedures and in further introducing online closed-loop corrections of the treatment.