Fast Localization and Segmentation of Tissue Abnormalities by Autonomous Robotic Palpation

Yan, Youcan; Pan, Jia

doi:10.1109/lra.2021.3058870

Cited by 26 publications

(13 citation statements)

References 23 publications

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“…BO has also allowed for rapidly mapping residual network function in stroke 15 or an efficient design of transcatheter aortic valve leaflets and optimisation of their geometry 16 . BO has been also used in the context of computer‐aided (or robot‐assisted) surgery 17,18 . Another strand of literature has applied BO for efficient parameter inference for finite‐element problems, for example in haemodynamics, 19 for learning material property of atherosclerotic carotid arteries, 20 or in cardiology 21 .…”

Section: Introductionmentioning

confidence: 99%

“…16 BO has been also used in the context of computer-aided (or robot-assisted) surgery. 17,18 Another strand of literature has applied BO for efficient parameter inference for finite-element problems, for example in haemodynamics, 19 for learning material property of atherosclerotic carotid arteries, 20 or in cardiology. 21 The latter study of Fan et al 21 is most closely related to our work as it has combined finite element modelling and BO to characterise exercise-induced myocardium growth to infer two unknown growth parameters.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

Borowska

Gao

Lazarus

et al. 2022

Numer Methods Biomed Eng

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We consider parameter inference in cardio‐mechanic models of the left ventricle, in particular the one based on the Holtzapfel‐Ogden (HO) constitutive law, using clinical in vivo data. The equations underlying these models do not admit closed form solutions and hence need to be solved numerically. These numerical procedures are computationally expensive making computational run times associated with numerical optimisation or sampling excessive for the uptake of the models in the clinical practice. To address this issue, we adopt the framework of Bayesian optimisation (BO), which is an efficient statistical technique of global optimisation. BO seeks the optimum of an unknown black‐box function by sequentially training a statistical surrogate‐model and using it to select the next query point by leveraging the associated exploration‐exploitation trade‐off. To guarantee that the estimates based on the in vivo data are realistic also for high‐pressures, unobservable in vivo, we include a penalty term based on a previously published empirical law developed using ex vivo data. Two case studies based on real data demonstrate that the proposed BO procedure outperforms the state‐of‐the‐art inference algorithm for the HO constitutive law.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

Borowska

Gao

Lazarus

et al. 2022

Numer Methods Biomed Eng

View full text Add to dashboard Cite

show abstract

“…There is an interesting analogy between this problem and the identification of the mechanical properties of human tissue, which has been extensively explored in previous studies. [104][105][106][107][108][109][110] In these studies, by mechanically perturbing the human tissue and observing its response, these groups were able to identify the tissue's mechanical properties. In order to identify the tissue's optical properties, the material would instead be excited by a laser pulse and its thermal response would be measured.…”

Section: Open Challengesmentioning

confidence: 99%

When the End Effector Is a Laser: A Review of Robotics in Laser Surgery

Lee

Pacheco

Fichera

et al. 2022

Advanced Intelligent Systems

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Combining laser technology with robotic precision and accuracy promises to introduce significant advances in minimally invasive surgical interventions. Lasers have already become a widespread tool in numerous surgical applications. They are proposed as a replacement for traditional tools (i.e., scalpels and electrocautery devices) to minimize surgical trauma, decrease healing times, and reduce the risk of postoperative complications. Compared to other energy sources, laser energy is wavelength‐dependent, allowing for preferential energy absorption in specific tissue types. This potentially leads to minimizing damage to healthy tissue and increasing surgical outcomes control and quality. Merging robotic control with laser techniques can help physicians achieve more accurate laser aiming and pave the way to automatic control of laser–tissue interactions in closed loop. Herein, a review of the state‐of‐the‐art robotic systems for laser surgery is presented. The goals of this paper are to present recent contributions in advanced intelligent systems for robot‐assisted laser surgery, provide readers with a better understanding of laser optics and the physics of laser–tissue interactions, discuss clinical applications of lasers in surgery, and provide guidance for future systems design.

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“…As a critical step of medical diagnostic and surgical procedures, further investigation is needed for accurate and efficient soft tissue sensing, also a key component of autonomous robotic surgery in the future. 1…”

Section: Introductionmentioning

confidence: 99%

Piezoresistivity modeling of soft tissue electrical-mechanical properties: A validation study

Guo

et al. 2023

Proc Inst Mech Eng H

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In general, the electrical property of soft tissues is sensitive to the force applied to their surface. To further study the relationship between the force and the electrical property of soft tissues, this paper attempts to investigate the effect of static and higher-order stresses on electrical properties. Overall, a practical experimental platform is designed to acquire the force information and the electrical property of soft tissues during a contact procedure, which is featured different compression stimuli, such as constant pressing force, constant pressing speed, and step-force compression, etc. Furthermore, the piezoresistive characteristic is innovatively introduced to model the mechanical-electrical properties of soft tissue. Finite Element Modeling (FEM) is adopted to fit the static piezoresistivity of the soft tissue. Finally, experimental studies were performed to demonstrate the effect of stress on the electrical properties and the feasibility of the proposed piezoresistive model to describe soft tissues’ mechanical and electrical properties.

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Fast Localization and Segmentation of Tissue Abnormalities by Autonomous Robotic Palpation

Cited by 26 publications

References 23 publications

Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

When the End Effector Is a Laser: A Review of Robotics in Laser Surgery

Piezoresistivity modeling of soft tissue electrical-mechanical properties: A validation study

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