Improved knot-tying methods for autonomous robot surgery

Chow, Der-Lin; Newman, Wyatt S.

doi:10.1109/coase.2013.6653955

Cited by 30 publications

(17 citation statements)

References 7 publications

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“…Despite the great interest on autonomy in surgical robotics, demonstrated by the amount of literature [11], research on soft tissues manipulation is limited. The vast majority of the literature focuses on the automation of tasks [12] involving extraneous elements such as suturing [13], [14] and interventional needle passing [8] [15]. On the other hand, automation of tasks that involve tissue manipulation are challenging due to the complex geometry and compliance of the soft tissues.…”

Section: A Technical Contributionmentioning

confidence: 99%

A Comparative Study of Spatio-Temporal U-Nets for Tissue Segmentation in Surgical Robotics

Attanasio

Alberti

Scaglioni

et al. 2021

IEEE Trans. Med. Robot. Bionics

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In surgical robotics, the ability to achieve high levels of autonomy is often limited by the complexity of the surgical scene. Autonomous interaction with soft tissues requires machines able to examine and understand the endoscopic video streams in real-time and identify the features of interest. In this work, we show the first example of spatio-temporal neural networks, based on the U-Net, aimed at segmenting soft tissues in endoscopic images. The networks, equipped with Long Short-Term Memory and Attention Gate cells, can extract the correlation between consecutive frames in an endoscopic video stream, thus enhancing the segmentation's accuracy with respect to the standard U-Net. Initially, three configurations of the spatiotemporal layers are compared to select the best architecture. Afterwards, the parameters of the network are optimised and finally the results are compared with the standard U-Net. An accuracy of 83.77% ± 2.18% and a precision of 78.42% ± 7.38% are achieved by implementing both Long Short Term Memory (LSTM) convolutional layers and Attention Gate blocks. The results, although originated in the context of surgical tissue retraction, could benefit many autonomous tasks such as ablation, suturing and debridement.

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Section: A Technical Contributionmentioning

confidence: 99%

A Comparative Study of Spatio-Temporal U-Nets for Tissue Segmentation in Surgical Robotics

Attanasio

Alberti

Scaglioni

et al. 2021

IEEE Trans. Med. Robot. Bionics

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show abstract

“…Adicionalmente están los robots semiautónomos o supervisados donde el operador interviene eventualmente para corregir acciones erradas, de igual manera pueden tener control compartido o co-worker [10], [11] para solventar las limitaciones y requerimientos en el quirófano, y finalmente se encuentran los sistemas autónomos, lo cual es una tendencia reciente. En la actualidad la inteligencia artificial provee la capacidad de tomar decisiones y realizar tareas de manera independiente [12], tal es el caso del sistema Star, capacitado para desarrollar de forma autónoma tareas sobre tejido blando [13].…”

Section: Robotica Quirurgicaunclassified

Robótica en cirugía y neurocirugía, aplicaciones y desafíos, una revisión

Rosero

Albán

2020

Sci. tech

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La integración de robots en los quirófanos plantea mejorar el desempeño y eficiencia de variados procedimientos, dado que ofrece ventajas destacables sobre los procedimientos convencionales, en particular la precisión, el filtrado de temblor de mano y la posibilidad de ejecución de tareas complejas, sin embargo, aún prevalecen considerables desafíos que afectan la masificación y la maniobrabilidad por parte de los cirujanos. En el presente trabajo se realiza una revisión del estado actual de la cirugía robótica, los retos y las tendencias. En concreto se evidencia la necesidad de mecanismos de realimentación de fuerza óptimos, así como la visualización dinámica mediante realidad aumentada o realidad virtual. Aun no es posible determinar que la cirugía robótica ha alcanzado estándares, sin embargo, la integración de tecnologías alternas permitirá mejorar no solo la eficiencia en cuanto al robot sino respecto de su operación por parte de los cirujanos.

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“…In this paper, a rolling arc looping knot tying trajectory specially designed for autonomous robotic surgery proposed by Chow et al . [34, 35] is used. This knot-tying motion planning method proposes a series of coordinated actions for a pair of manipulators for automatically tying a surgeon’s knot.…”

Section: Problem Statement and Formulationmentioning

confidence: 99%

“…The force requirements during the knot tying part of the suturing task are ignored, as the force requirements for knot tying are substantially smaller than the force required during the needle driving. The explicit details of the reference suturing trajectory can be found in [26, 27, 34, 35]. …”

Section: Problem Statement and Formulationmentioning

confidence: 99%

Needle Grasp and Entry Port Selection for Automatic Execution of Suturing Tasks inRobotic Minimally Invasive Surgery

Liu

Çavuşoğlu

2016

IEEE Trans. Automat. Sci. Eng.

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This paper presents algorithms for selection of needle grasp and for selection of entry ports of robotic instruments, for autonomous robotic execution of the minimally invasive surgical suturing task. A critical issue for automatic execution of surgical tasks, such as suturing, is the choice of needle grasp for the robotic system. Inappropriate needle grasp increases operating time requiring multiple regrasps to complete the desired task. In robotic minimally invasive surgery, the entry port that the surgical robot goes through into the patient’s body has a significant role on the performance of the robot. Improper entry port affects the robot’s dexterity, manipulability and reachability. The proposed methods use manipulability, dexterity and torque metrics for needle grasp selection, and employ needle grasp robustness and target location robustness metrics for port selection. The results of a case study simulation in thoracoscopic surgery is also presented to demonstrate the proposed methods. Note to Practitioners—This paper is motivated by the problem of automating low-level surgical tasks in robotic surgery, such as, suturing, retraction, dissection, and providing exposure. Specifically, this paper focuses on needle grasp and entry port selection for automating robotic surgical suturing. Selection of an appropriate way of grasping a needle is critical for successfully and robustly completing autonomous suturing. To the best authors’ knowledge, there are no earlier studies in the literature which focus on the needle grasp selection problem. The proposed approach determines how to grasp the needle by optimizing the surgical system’s manipulation performance. The existing approaches in the literature for selecting entry ports for the robotic surgical tools only consider the teleoperated robotic minimally invasive surgery, in which the surgeons directly control the robotic instruments. However, automated performance of suturing introduces additional challenges due to uncertainties in needle localization and grasping. This paper proposes two new performance metrics on selecting port locations from the perspective of autonomously performing surgical suturing, without direct involvement of the human user. The paper also presents preliminary experiments which demonstrate the effectiveness of the proposed methods.

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Improved knot-tying methods for autonomous robot surgery

Cited by 30 publications

References 7 publications

A Comparative Study of Spatio-Temporal U-Nets for Tissue Segmentation in Surgical Robotics

A Comparative Study of Spatio-Temporal U-Nets for Tissue Segmentation in Surgical Robotics

Robótica en cirugía y neurocirugía, aplicaciones y desafíos, una revisión

Needle Grasp and Entry Port Selection for Automatic Execution of Suturing Tasks inRobotic Minimally Invasive Surgery

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