A virtual scalpel system for computer-assisted laser microsurgery

Mattos, Leonardo S.; Dagnino, Giulio; Becattini, Gabriele; Dellepiane, Massimo; Caldwell, Darwin G.

doi:10.1109/iros.2011.6094574

Cited by 33 publications

(43 citation statements)

References 10 publications

(9 reference statements)

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“…movements of the laser beam along a trajectory on the surface of the tissue. The robotic platform used in this research [6,7] offers automatic laser scanning, allowing for fast scans at a controlled frequency. Prior research has shown that there is a correlation between the speed of motion of the laser and the resulting depth of incision in hard tissue [4].…”

Section: Influence Of Scanning Frequencymentioning

confidence: 99%

Modeling the Laser Ablation Process

Fichera

2016

Springer Theses

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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.Multiple parameters influence the laser ablation process. With regard to the surgical equipment in use today, these are laser power, delivery mode, pulse duration, scanning frequency. To fully understand the effects of these parameters, first we report on controlled experiments where only one parameter at a time is modified and the resulting depth of incision is examined.The incision depth is modeled as a function of the laser exposure time. The inverse model is also extracted, which allows to calculate the exposure time required to reach a given incision depth. This inverse model is used in a feed forward setting, to prove the concept of the automatic incision of soft tissue. In addition, we demonstrate how the model can be used to implement the automatic ablation of entire volumes of tissue, through the superposition of controlled laser incisions. The chapter is concluded by a discussion of the findings for the depth estimation model, whose accuracy is considered from a clinical perspective.

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Section: Influence Of Scanning Frequencymentioning

confidence: 99%

Modeling the Laser Ablation Process

Fichera

2016

Springer Theses

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“…Laser scanning, as described in [25], was used for this work: motorized mirrors are used to deflect the laser beam, enabling the automatic execution of preprogrammed cutting patterns. High-frequency cycles of the laser motion across the target tissue remove overlying layers with each pass.…”

Section: Controlled Incision Of Soft Tissuementioning

confidence: 99%

“…A motorized micromanipulator system previously developed in our laboratory [25] provides the controlled motion of the laser. This device regulates the motion of the laser through a tip/tilt fast steering mirror (S-334 manufactured by PI GmbH, Germany), with a maximum accuracy of 4 µm at a distance of 400 mm from the target (typical operating distance).…”

Section: Controlled Incision Of Soft Tissuementioning

confidence: 99%

Cognitive Supervision for Transoral Laser Microsurgery

Fichera

2016

Springer Theses

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The thermal laser-tissue interactions described in Chap. 2 constitute the basic building block of laser microsurgery. In particular, ablation by vaporization is the process by means of which laser incisions and resections are performed. As we shall see in this chapter, these interactions need to be carefully monitored to ensure the formation of incisions as planned by the surgeon. Control of the laser effects on tissue is essential for the purpose of ensuring a safe and efficient surgical performance, which encompasses both resection accuracy and limited thermal damage to underlying and surrounding tissues.Despite its importance, the control of the laser effects on tissues during Transoral Laser Microsurgery (TLM) is still performed manually, since available technologies do not include any support to monitor the state of tissues under laser irradiation. When analyzing the workflow of these interventions, it becomes apparent that the quality of laser resections depends entirely on clinicians, who must possess the experience required to anticipate and understand the results of their laser actions.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.The first two sections of this chapter describe the current workflow of TLM and discuss its limitations from a clinical perspective. Our analysis is based both on evidence reported in medical literature, as well as on the opinions of clinicians who were consulted in the course of this doctoral research. In Sect. 3.3, we formulate the concept of a system capable of assisting clinicians during TLM, enhancing their perception of laser-induced effects on tissues. Two specific effects: thermal (temperature of tissues) and mechanical (laser cutting depth). We will review existing approaches to monitor these effects during laser irradiation, focusing on considerations regarding their

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“…The new intraoperative surgical planning system is based on the robot-assisted laser microsurgery system developed at the IIT [8]. This system allows precise surgical laser aiming and activation from an intuitive teleoperation interface using the virtual scalpel concept.…”

Section: System Architecturementioning

confidence: 99%

“…For this reason, our recent research efforts have focused in this area and a new teleoperated laser microsurgery system has been developed [8]. This system is controlled from an intuitive and ergonomic teleoperation interface using the virtual scalpel mode, which allows surgeons to perform operations using a stylus directly over the live video of the surgical site.…”

Section: Introductionmentioning

confidence: 99%

Safe teleoperation based on flexible intraoperative planning for robot-assisted laser microsurgery

Mattos

Caldwell

2012

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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This paper describes a new intraoperative planning system created to improve precision and safety in teleoperated laser microsurgeries. It addresses major safety issues related to real-time control of a surgical laser during teleoperated procedures, which are related to the reliability and robustness of the telecommunication channels. Here, a safe solution is presented, consisting in a new planning system architecture that maintains the flexibility and benefits of real-time teleoperation and keeps the surgeon in control of all surgical actions. The developed system is based on our virtual scalpel system for robot-assisted laser microsurgery, and allows the intuitive use of stylus to create surgical plans directly over live video of the surgical field. In this case, surgical plans are defined as graphic objects overlaid on the live video, which can be easily modified or replaced as needed, and which are transmitted to the main surgical system controller for subsequent safe execution. In the process of improving safety, this new planning system also resulted in improved laser aiming precision and improved capability for higher quality laser procedures, both due to the new surgical plan execution module, which allows very fast and precise laser aiming control. Experimental results presented herein show that, in addition to the safety improvements, the new planning system resulted in a 48% improvement in laser aiming precision when compared to the previous virtual scalpel system.

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A virtual scalpel system for computer-assisted laser microsurgery

Cited by 33 publications

References 10 publications

Modeling the Laser Ablation Process

Modeling the Laser Ablation Process

Cognitive Supervision for Transoral Laser Microsurgery

Safe teleoperation based on flexible intraoperative planning for robot-assisted laser microsurgery

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