Robot-Assisted Minimally Invasive Surgery—Surgical Robotics in the Data Age

Proceedings of the IEEE, Journal Year: 2022, Volume and Issue: 110(7), P. 835 - 846

Published: June 23, 2022

Telesurgical robotics, as a technical solution for robot-assisted minimally invasive surgery (RAMIS), has become the first domain within medicosurgical robotics that achieved true global clinical adoption. Its relative success (still at low single-digit percentile total market penetration) roots in particular human-in-the-loop control, which trained surgeon is always kept responsible outcome by robot-actuated tools. Nowadays, this paradigm challenged need improved surgical performance, traceability, and safety reaching beyond human capabilities. Partially due to complexity financial burden, adoption of telesurgical not reached its full potential, far. Apart from absolutely market-dominating da Vinci system, there are already 60+ emerging RAMIS robot types, out 15 have some form regulatory clearance. This article aims connect technological advancement with principles commercialization, particularly looking engineering components under development potential bring significant advantages practice. Current robots often do exceed functionalities deriving their mechatronics, lack data-driven assistance smart human–machine collaboration. Computer gradually gaining more significance systems. Enhanced manipulation capabilities, refined sensors, advanced vision, task-level automation, features, data integration mark together inception new era infiltrated machine learning (ML) artificial intelligence (AI) solutions. Observing other domains, it definite key requirement robust AI good quality data, derived proper acquisition sharing allow building solutions real time based on ML. Emerging technologies reviewed both historical future perspective.

Language: Английский

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Computer vision in surgery: from potential to clinical value

npj Digital Medicine, Journal Year: 2022, Volume and Issue: 5(1)

Published: Oct. 28, 2022

Abstract Hundreds of millions operations are performed worldwide each year, and the rising uptake in minimally invasive surgery has enabled fiber optic cameras robots to become both important tools conduct sensors from which capture information about surgery. Computer vision (CV), application algorithms analyze interpret visual data, a critical technology through study intraoperative phase care with goals augmenting surgeons’ decision-making processes, supporting safer surgery, expanding access surgical care. While much work been on potential use cases, there currently no CV widely used for diagnostic or therapeutic applications Using laparoscopic cholecystectomy as an example, we reviewed current techniques that have applied their clinical applications. Finally, discuss challenges obstacles remain be overcome broader implementation adoption

Language: Английский

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Machine learning for technical skill assessment in surgery: a systematic review

npj Digital Medicine, Journal Year: 2022, Volume and Issue: 5(1)

Published: March 3, 2022

Accurate and objective performance assessment is essential for both trainees certified surgeons. However, existing methods can be time consuming, labor intensive, subject to bias. Machine learning (ML) has the potential provide rapid, automated, reproducible feedback without need expert reviewers. We aimed systematically review literature determine ML techniques used technical surgical skill identify challenges barriers in field. A systematic search, accordance with PRISMA statement, was performed studies detailing use of surgery. Of 1896 that were retrieved, 66 included. The most common Hidden Markov Models (HMM, 14/66), Support Vector Machines (SVM, 17/66), Artificial Neural Networks (ANN, 17/66). 40/66 kinematic data, 19/66 video or image 7/66 both. Studies assessed benchtop tasks (48/66), simulator (10/66), real-life surgery (8/66). Accuracy rates over 80% achieved, although participants varied between studies. Barriers progress field included a focus on basic tasks, lack standardization studies, datasets. produce accurate through including HMM, SVM, ANN. Future ML-based tools should move beyond towards interpretable clinical value surgeon.PROSPERO: CRD42020226071.

Language: Английский

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Artificial intelligence in surgery

Nature Medicine, Journal Year: 2024, Volume and Issue: 30(5), P. 1257 - 1268

Published: May 1, 2024

Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications surgery remain relatively nascent. Here we review the integration of AI field surgery, centering our discussion on multifaceted improvements surgical care preoperative, intraoperative and postoperative space. The emergence foundation model architectures, wearable technologies improving data infrastructures enabling rapid advances interventions utility. We discuss how maturing methods hold potential to improve patient outcomes, facilitate education optimize care. current deep learning approaches outline a vision for future through multimodal models. This Review outlines state art artificial settings, where it has enormous system efficiencies.

Language: Английский

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Labelling instructions matter in biomedical image analysis

Nature Machine Intelligence, Journal Year: 2023, Volume and Issue: 5(3), P. 273 - 283

Published: March 2, 2023

Abstract Biomedical image analysis algorithm validation depends on high-quality annotation of reference datasets, for which labelling instructions are key. Despite their importance, optimization remains largely unexplored. Here we present a systematic study and impact quality in the field. Through comprehensive examination professional practice international competitions registered at Medical Image Computing Computer Assisted Intervention Society, largest society biomedical imaging field, uncovered discrepancy between annotators’ needs current availability. On basis an 14,040 images annotated by 156 annotators from four companies 708 Amazon Mechanical Turk crowdworkers using with different information density levels, further found that including exemplary substantially boosts performance compared text-only descriptions, while solely extending text descriptions does not. Finally, constantly outperform crowdworkers. Our raises awareness need standards instructions.

Language: Английский

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Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark

Medical Image Analysis, Journal Year: 2023, Volume and Issue: 86, P. 102770 - 102770

Published: Feb. 22, 2023

Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase safety operation through context-sensitive warnings semi-autonomous robotic or improve training surgeons via data-driven feedback. In up to 91% average precision has been reported phase recognition on an open data single-center video dataset. this work we investigated generalizability algorithms in a multicenter setting including more difficult tasks such as action skill.To achieve goal, dataset with 33 laparoscopic cholecystectomy videos from three centers total time 22 h was created. Labels included framewise annotation seven phases 250 transitions, 5514 occurences four actions, 6980 21 instruments instrument categories 495 classifications five dimensions. The used 2019 international Endoscopic Vision challenge, sub-challenge analysis. Here, 12 research teams trained submitted their machine learning phase, action, and/or assessment.F1-scores were achieved between 23.9% 67.7% (n = 9 teams), presence detection 38.5% 63.8% 8 but only 21.8% 23.3% 5 teams). absolute error assessment 0.78 1 team).Surgical promising support team, there is still room improvement, shown by our comparison algorithms. This novel HeiChole benchmark can be comparable evaluation validation future work. studies, it utmost importance create open, high-quality datasets order allow development artificial intelligence robotics surgery.

Language: Английский

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Assertiveness-based Agent Communication for a Personalized Medicine on Medical Imaging Diagnosis

Published: April 19, 2023

Intelligent agents are showing increasing promise for clinical decision-making in a variety of healthcare settings. While substantial body work has contributed to the best strategies convey these agents' decisions clinicians, few have considered impact personalizing and customizing communications on clinicians' performance receptiveness. This raises question how intelligent should adapt their tone accordance with target audience. We designed two approaches communicate an agent breast cancer diagnosis different tones: suggestive (non-assertive) imposing (assertive) one. used inform about: (1) number detected findings; (2) severity each per medical imaging modality; (3) visual scale representing estimates; (4) sensitivity specificity agent; (5) arguments patient, such as pathological co-variables. Our results demonstrate that assertiveness plays important role this communication is perceived its benefits. show according professional experience clinician can reduce errors increase satisfaction, bringing novel perspective design adaptive between clinicians.

Language: Английский

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Technical and ethical considerations in telesurgery

Journal of Robotic Surgery, Journal Year: 2024, Volume and Issue: 18(1)

Published: Jan. 17, 2024

Language: Английский

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Innovations in Minimally Invasive Surgery

Advances in healthcare information systems and administration book series, Journal Year: 2024, Volume and Issue: unknown, P. 110 - 131

Published: Feb. 14, 2024

The field of surgical robotics has been rapidly advancing, with a focus on improving minimally invasive surgery techniques. Minimally (MIS) is characterized by smaller incisions, reduced trauma to the patient, quicker recovery times, and less post-operative pain compared traditional open surgery. Surgical robots have played significant role in enhancing capabilities surgeons expanding potential for MIS. next era smart flexible MIS could encompass several exciting developments. Future are likely be more adaptable, allowing them navigate complex anatomical structures greater ease. In this chapter, authors will present current state-of-the-art robotic applications MIS, focusing limitations challenges still their use clinical applications. This chapter as it not only offers insights into technological advancements but also lays groundwork understanding future innovations that revolutionize patient care

Language: Английский

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Tracking and mapping in medical computer vision: A review

Medical Image Analysis, Journal Year: 2024, Volume and Issue: 94, P. 103131 - 103131

Published: March 2, 2024

As computer vision algorithms increase in capability, their applications clinical systems will become more pervasive. These include: diagnostics, such as colonoscopy and bronchoscopy; guiding biopsies, minimally invasive interventions, surgery; automating instrument motion; providing image guidance using pre-operative scans. Many of these depend on the specific visual nature medical scenes require designing to perform this environment. In review, we provide an update field camera-based tracking scene mapping surgery diagnostics vision. We begin with describing our review process, which results a final list 515 papers that cover. then give high-level summary state art relevant background for those who need applications. After which, datasets provided needs motivate design. Then, delve into algorithmic side, summarize recent developments. This should be especially useful algorithm designers looking understand capability off-the-shelf methods. maintain focus deformable environments while also reviewing essential building blocks rigid since there is large amount crossover With summarized, discuss current methods along future algorithms, quantification, viability some research directions questions. conclude new designed or combined support environments, put collecting training evaluation.

Language: Английский

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