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Vision Based Surgical Tool Tracking With Robot Kinematics Prior
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Book Synopsis Vision Based Surgical Tool Tracking with Robot Kinematics Prior by : Yun-Hsuan Su
Download or read book Vision Based Surgical Tool Tracking with Robot Kinematics Prior written by Yun-Hsuan Su and published by . This book was released on 2017 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robot assisted minimally invasive surgery combines the skill and techniques of highly-trained surgeons with the robustness and precision of machines. Through a teleoperation scheme, surgeons can execute high-level surgical tasks by commanding instruments controlled by precise robotic devices. Several advantages arise. To name a few: (1) achieved precision is beyond that of human dexterity alone (2) a greater number of kinematic degrees of freedom are possible at the surgical tool tip (3) surgeons are able to operate remotely, i.e. agnostic of patient location given a suitable communication line. Despite the numerous advantages over traditional key-hole or laparoscopic surgery, the lack of realistic and real-time force feedback is a major drawback --- discerning tool-tissue interactions can be unintuitive and can ultimately result in unintentional tissue damage. Directly sensing forces at the tool-tissue interface is theoretically possible using tool tip mounted force sensors, but this approach is not amenable to required sterilization procedures. Thus, a vision based force estimation method is proposed to infer the applied force based on real-time analysis of tissue deformation.
Book Synopsis Vision Based Surgical Tool Tracking and Force Estimation with Robot Kinematics Prior by : Yun-Hsuan Su
Download or read book Vision Based Surgical Tool Tracking and Force Estimation with Robot Kinematics Prior written by Yun-Hsuan Su and published by . This book was released on 2020 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robot assisted minimally invasive surgery combines the skill and techniques of highly-trained surgeons with the robustness and precision of machines. Through a teleoperation scheme, surgeons can execute high-level surgical tasks by commanding instruments controlled by precise robotic devices. Several advantages arise. To name a few: (1) achieved precision is beyond that of human dexterity alone (2) a greater number of kinematic degrees of freedom are possible at the surgical tool tip (3) surgeons are able to operate remotely, i.e. agnostic of patient location given a suitable communication line. Despite the numerous advantages over traditional key-hole or laparoscopic surgery, the lack of realistic and real-time force feedback is a major drawback --- discerning tool-tissue interactions can be unintuitive and can ultimately result in unintentional tissue damage. Directly sensing forces at the tool-tissue interface is theoretically possible using tool tip mounted force sensors, but this approach is not amenable to required sterilization procedures. Thus, a vision based force estimation method is proposed to infer the applied force based on real-time analysis of tissue deformation.
Book Synopsis Visual Tracking in Conventional Minimally Invasive Surgery by : Shahram Payandeh
Download or read book Visual Tracking in Conventional Minimally Invasive Surgery written by Shahram Payandeh and published by CRC Press. This book was released on 2016-11-03 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual Tracking in Conventional Minimally Invasive Surgery introduces the various tools and methodologies that can be used to enhance a conventional surgical setup with some degree of automation. The main focus of this book is on methods for tracking surgical tools and how they can be used to assist the surgeon during the surgical operation. Various notions associated with surgeon–computer interfaces and image-guided navigation are explored, with a range of experimental results. The book starts with some basic motivations for minimally invasive surgery and states the various distinctions between robotic and non-robotic (conventional) versions of this procedure. Common components of this type of operation are presented with a review of the literature addressing the automation aspects of such a setup. Examples of tracking results are shown for both motion and gesture recognition of surgical tools, which can be used as part of the surgeon–computer interface. In the case of marker-less tracking, where no special visual markers can be added to the surgical tools, the tracking results are divided into two types of methodology, depending on the nature and the estimate of the visual noise. Details of the tracking methods are presented using standard Kalman filters and particle filters. The last part of the book provides approaches for tracking a region on the surgical scene defined by the surgeon. Examples of how these tracking approaches can be used as part of image-guided navigation are demonstrated. This book is designed for control engineers interested in visual tracking, computer vision researchers and system designers involved with surgical automation, as well as surgeons, biomedical engineers, and robotic researchers.
Book Synopsis Vision-based Surgical Tool Pose Estimation for Da Vinci Robotic System by : Hao Ran
Download or read book Vision-based Surgical Tool Pose Estimation for Da Vinci Robotic System written by Hao Ran and published by . This book was released on 2017 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis explores Bayesian filtering based methods for surgical tool tracking using stereo vision. The tool geometry and silhouette generating algorithm are defined based on the surgical tool model. A virtual rendering algorithm is proposed to create the virtual images by rendering the silhouette of the defined tool geometry under the stereo cameras. Both parametric and nonparametric filtering algorithms are explored for 9-degree of freedom surgical tool tracking, represented by Particle Filter and Unscented Kalman Filter respectively. The tracking performances for both Particle Filter and Unscented Kalman Filter are evaluated on da Vinci surgical robotic system and the da Vinci simulation environment (Gazebo) through Robot Operating System (ROS).
Book Synopsis Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 by : Linwei Wang
Download or read book Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 written by Linwei Wang and published by Springer Nature. This book was released on 2022-09-16 with total page 809 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization; Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.
Book Synopsis Handbook of Robotic and Image-Guided Surgery by : Mohammad Abedin-Nasab
Download or read book Handbook of Robotic and Image-Guided Surgery written by Mohammad Abedin-Nasab and published by Elsevier. This book was released on 2019-09-25 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Robotic and Image-Guided Surgery provides state-of-the-art systems and methods for robotic and computer-assisted surgeries. In this masterpiece, contributions of 169 researchers from 19 countries have been gathered to provide 38 chapters. This handbook is 744 pages, includes 659 figures and 61 videos. It also provides basic medical knowledge for engineers and basic engineering principles for surgeons. A key strength of this text is the fusion of engineering, radiology, and surgical principles into one book. A thorough and in-depth handbook on surgical robotics and image-guided surgery which includes both fundamentals and advances in the field A comprehensive reference on robot-assisted laparoscopic, orthopedic, and head-and-neck surgeries Chapters are contributed by worldwide experts from both engineering and surgical backgrounds
Book Synopsis Computer Vision And Robotics In Perioperative Process by : Yi Xu
Download or read book Computer Vision And Robotics In Perioperative Process written by Yi Xu and published by World Scientific. This book was released on 2018-04-10 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable compendium highlights the challenges of perioperative process in hospitals today. It delves into the development of a multi-agent robotic system where a dirty-side robot that sorts instruments returned from a surgical room into different containers for easy scrubbing, a Traybot that navigates the environment and transports the instrument containers to different stations, a clean-side robot that picks up instruments and places them in surgical kits, and an orchestration software architecture that manages the cooperation between different robots.The book discusses the technical details of all the components, from system architecture to the details of the end-effector design. Readers will gain significant knowledge on how such a system was put together.Related Link(s)
Book Synopsis Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 by : Sebastien Ourselin
Download or read book Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 written by Sebastien Ourselin and published by Springer. This book was released on 2016-10-17 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis; brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation; shape modeling; cardiac and vascular image analysis; image reconstruction; and MR image analysis.
Book Synopsis Vision Based Sensor Substitution in Robotic Assisted Surgery by : Arturo Marbán González
Download or read book Vision Based Sensor Substitution in Robotic Assisted Surgery written by Arturo Marbán González and published by . This book was released on 2019 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perceiving and understanding the world represents a long-term goal in the field of Artificial Intelligence (AI). In recent years, advances in the field of Machine Learning (ML), and specifically in Deep Learning (DL), have led to the development of powerful models based on Deep Neural Networks (DNN) capable of interpreting high dimensional data, leading to higher performance in perception related tasks. DNNs designed in a Supervised Learning (SL) setting, such as Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) networks, greatly contribute to the state of the art in image recognition and in the processing of long sequences of data, respectively. This is because CNNs excel in modeling data with spatial structure, and LSTM networks highlight in modeling data with temporal structure. They both represent the building blocks for modeling the spatio-temporal structure of data such as video sequences. Nonetheless, these models have not been exploited in the medical domain, where images and video sequences are frequently available, that is, in Minimally Invasive Surgery (MIS). Furthermore, most of the research going on rely on the design of DNNs used as classifiers (i.e. the output is a discrete category) rather than regressors (i.e. the output is a set of continuous real values). Recently, in the context of Unsupervised Learning (UL), Generative Adversarial Networks (GAN) have gained popularity as a powerful framework to design generative models. GANs consist of two models, a Generator Neural Network (G) and a Discriminator Neural Network (D), each one with a different objective. Samples produced by G have a distribution PG, while those that come from ground-truth data have a distribution PDATA. The task of D is to classify samples from ground-truth data and those rendered by G as real and fake, respectively. On the other hand, the objective of G is to "fool" D, by learning to generate samples that resemble the ground-truth data. As the training process evolves, G learns the distribution of PDATA. This framework is flexible and can be applied to different neural network architectures, such as in Convolutional Auto-Encoders (CAE), resulting in better image reconstruction quality In this dissertation, a regression model based on DNNs is described, with applications in the context of Robot-Assisted Minimally Invasive Surgery (RAMIS). First, this model is developed in a SL setting. Subsequently, it is extended to a Semi-Supervised Learning (SSL) approach by using a CAE and leveraging the advantages of the GAN framework. The regression model is designed to learn a complex relationship between video sequences (as input data) and the evolution of continuous variables over time (as output data). The objective of this research is to perform Vision Based Sensor Substitution (VBSS). Therefore, the DNN constitutes a "virtual sensor" that estimates the evolution of physical variables over time. The target applications are those where the only allowed sensor consists of a camera system (monocular/stereo) and other electronic sensor devices are constrained. In the context of RAMIS, endowing robotic systems with force feedback capability represents a great help to provide the surgeon with an essential information for a better performance. Specifically, the estimation of interaction forces between surgical instruments and biological materials, such as soft-tissues, is addressed in this dissertation. In RAMIS scenarios, the only available sensor is the camera (i.e. monocular/stereo endoscope), which provides data easy to record (i.e. video sequences), but its interpretation is challenging. Therefore, a DNN is presented in this work as a regression model that implements the concept of Sensorless Force Estimation (SFE) under a Vision Based (VB) approach. In this approach, interaction forces are estimated from video sequences (as continuous time-varying signals), instead of relying on the direct measurement by a sensor in contact with biological materials (i.e. soft tissue). The DNN described for this application is designed in a SL setting, and subsequently, it is extended to SSL. The regression model designed for SFE is generic enough to be used in other domains with equivalent mathematical formulation. Therefore, it has also been studied and evaluated in the application of surgical instruments tracking. Specifically, in the estimation of the tooltip position and velocity (in 3D space) from monocular video sequences. Such information is useful in tasks related to Surgical Gesture Classification (SGC). The regression model used in this application is described in a SL setting. The aim of this dissertation is to present DNNs as regression models in the context of RAMIS, being the target application VBSS. This approach has been studied in two mathematically equivalent problems (described above): (i) Vision-based SFE and (ii) surgical instruments tracking. Moreover, the results of this research suggest that the regression model is generic and robust enough to be used in both applications. Therefore, this model can be used to address problems in which the estimation of continuous time-varying signals from video sequences is required.
Book Synopsis Medicine Meets Virtual Reality 20 by : James D. Westwood
Download or read book Medicine Meets Virtual Reality 20 written by James D. Westwood and published by IOS Press. This book was released on 2013 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since 1992, when it began as the Medicine Meets Virtual Reality conference, NextMed/MMVR has been a forum for researchers utilizing IT advances to improve diagnosis and therapy, medical education, and procedural training. Scientists and engineers, physicians and other care providers, educators and students, military medicine specialists, futurists, and industry all come together with the shared goal of making healthcare more precise and effective.This book presents the proceedings of the 20th NextMed/MMVR conference, held in San Diego, California, USA, in February 2013. It covers a wide range of topics simulation, modeling,
Book Synopsis Visual Force Estimation in Robot-assisted Minimally Invasive Surgery by : Zonghe Chua
Download or read book Visual Force Estimation in Robot-assisted Minimally Invasive Surgery written by Zonghe Chua and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tissue handling and force sensitivity are important skills for surgeons to possess to conduct safe and effective surgery. In robot-assisted minimally invasive surgery (RMIS), where a surgeon teleoperates a multi-arm robot equipped with endoscopic tools without haptic feedback, surgeons rely heavily on visual feedback to estimate the amount of force they are applying to tissue. Thus, good tissue handling and force sensitivity in RMIS is difficult to achieve. To develop general surgical skill, researchers and surgical educators have provided objective performance measurement and multi-sensory training. However, attempts to do this for tissue handling have proven challenging. This dissertation presents work towards teaching and evaluating surgeon tissue handling ability in RMIS by studying how humans and machines can learn to estimate force visually. First, I present an experiment to understand how different forms of prior haptic experience inform a teleoperator's ability to perform visual force estimation for a previously learned task and an unseen task. The results of the experiment show that, for a retraction task on silicone samples, human teleoperators relied on a proprioception heuristic as opposed to a visually informed learned representation of tissue stiffness to perform the task. However, when performing visual force estimation during an unseen silicone palpation task, teleoperators who previously performed the silicone retraction task manually had the best speed-accuracy, suggesting that because they learned the visual force estimation task under the same motion scaling as other manipulations encountered in daily living, they successfully used that prior experience to improve their performance of the unseen task. Having shown that human teleoperators are able to learn how to estimate forces visually after training with haptic and visual feedback, I investigate if neural network systems can perform a similar form of visual force estimation. I present a multimodal neural network and a mock tissue manipulation dataset for performing visual force estimation. I evaluate the multimodal network, and its unimodal variants on their generalization performance over different viewpoints, unseen tools and unseen materials, as well as the contribution of different state inputs to the performance of the networks. I found that vision-based force estimation neural networks can generalize over changes in viewpoints and robot configurations, as well as unseen tools while having faster performance than existing recurrent neural networks. As expected, kinematic information was less useful for estimating force than joint torque or force information in networks that relied on robot state inputs. Including both types of inputs resulted in the best performance. Following this, I show how the neural network-based force estimates perform when used for real-time kinesthetic haptic feedback on an RMIS robot. I present a novel approach which models the teleoperation dynamics and measures stability using a passivity-based metric. Networks that used robot state inputs were more transparent but displayed lower stability compared to a network that only used visual inputs. Due to the inaccessibility of accurate end effector force sensing for RMIS tools, the studies above are limited to one-handed teleoperated manipulation. To address this hardware limitation, I present an open-source three-degree-of-freedom force sensor for bimanual RMIS research applications. I describe the theoretical principles behind the sensor design, as well as the manufacturing approaches that enable the sensors to be easily built and modified by other researchers in the field. I characterize the performance of the force sensor both as a standalone sensor and in a dual jaw set up mounted on an existing RMIS tool. I found that the sensor achieved an accuracy that was below what is detectable by human haptic perception in the range of forces typical of tissue manipulation. The design of the sensor was shown to be robust to manufacturing variations, maintaining desired accuracy over two separate builds of the sensor. When used in a dual jaw configuration, the sensor was also capable of measuring grip force in the range used for delicate tissue manipulation.
Book Synopsis Vision-based Control of a Handheld Micromanipulator for Robot-assisted Retinal Surgery by : Brian C. Becker
Download or read book Vision-based Control of a Handheld Micromanipulator for Robot-assisted Retinal Surgery written by Brian C. Becker and published by . This book was released on 2012 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Surgeons increasingly need to perform complex operations on extremely small anatomy. Many existing and promising new surgeries are effective, but difficult or impossible to perform because humans lack the extraordinary control required at sub-millimeter scales. Using micromanipulators, surgeons gain higher positioning accuracy and additional dexterity as the instrument removes tremor and scales hand motions. While these aids are advantageous, they do not actively consider the goals or intentions of the operator and thus cannot provide context-specific behaviors, such as motion scaling around anatomical targets, prevention of unwanted contact with pre-defined tissue areas, compensation for moving anatomy, and other helpful task-dependent actions. This thesis explores the fusion of visual information with micromanipulator control and enforces task-specific behaviors that respond in synergy with the surgeon's intentions and motions throughout surgical procedures. By exploiting real-time microscope view observations, a-priori knowledge of surgical operations, and pre-operative data prepared before the surgery, we hypothesize that micromanipulators can employ individualized and targeted aids to further help the surgeon. Specifically, we propose a vision-based control framework of virtual fixtures for handheld micromanipulator robots that naturally incorporates tremor suppression and motion scaling. We develop real-time vision systems to track the surgeon and anatomy and design fast, new algorithms for analysis of the retina. Virtual fixtures constructed from visually tracked anatomy allows for complex task-specific behaviors that monitor the surgeon's actions and react appropriately to cooperatively accomplish the procedure. Particular focus is given to vitreoretinal surgery as a good choice for vision-based control because several new and promising surgical techniques in the eye depend on fine manipulations of tiny and delicate retinal structures. Experiments with Micron, the fully handheld micromanipulator developed in our lab, show that vision-based virtual fixtures significantly increase pointing precision by reducing positioning error during synthetic, but medically relevant hold-still and tracing tasks. To evaluate the proposed framework in realistic environments, we consider three demanding retinal procedures: membrane peeling, laser photocoagulation, and vessel cannulation. Preclinical trials on artificial phantoms, ex vivo, and in vivo animal models demonstrate that vision-based control of a micromanipulator significantly improves surgeon performance (p
Book Synopsis Vision-based Surgical Instrument Segmentation and Endoscopic Sinus Surgery Skill Assessment by : Shan Lin
Download or read book Vision-based Surgical Instrument Segmentation and Endoscopic Sinus Surgery Skill Assessment written by Shan Lin and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In robot-assisted surgery, engineering technologies are applied to augment surgeons' ability to conduct safer surgeries and achieve better treatment outcomes. To provide appropriate assistance to the surgeons, the ability to understand surgical phases, and predict risks and remaining procedures is an enabling technology for next-generation autonomous surgical robots. Vision-based surgical instrument segmentation, which aims to identify instrument regions in surgical images, is one important task that can provide instrument location information to robotic systems. The potential uses of instrument segmentation results include surgical workflow analysis, risk supervision and prediction, and surgical skill assessment. Despite the wide range of potential applications of instrument segmentation, existing technologies are still not robust enough and lack generalizability when applied to highly dynamic surgical environments. In this dissertation, we develop a convolutional neural network that can aggregate video frame features temporally in a recurrent mode to achieve robust segmentation. Moreover, we explore transfer learning technologies that can improve segmentation performance on the target domains by leveraging knowledge learned from labeled source domains. Finally, we conduct several pilot experiments on vision-based, automatic and objective surgical skill assessment.
Book Synopsis Computer Vision by : Simon J. D. Prince
Download or read book Computer Vision written by Simon J. D. Prince and published by Cambridge University Press. This book was released on 2012-06-18 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Book Synopsis Advances in Mechanism and Machine Science by : Tadeusz Uhl
Download or read book Advances in Mechanism and Machine Science written by Tadeusz Uhl and published by Springer. This book was released on 2019-06-13 with total page 4248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 15th IFToMM World Congress, which was held in Krakow, Poland, from June 30 to July 4, 2019. Having been organized every four years since 1965, the Congress represents the world’s largest scientific event on mechanism and machine science (MMS). The contributions cover an extremely diverse range of topics, including biomechanical engineering, computational kinematics, design methodologies, dynamics of machinery, multibody dynamics, gearing and transmissions, history of MMS, linkage and mechanical controls, robotics and mechatronics, micro-mechanisms, reliability of machines and mechanisms, rotor dynamics, standardization of terminology, sustainable energy systems, transportation machinery, tribology and vibration. Selected by means of a rigorous international peer-review process, they highlight numerous exciting advances and ideas that will spur novel research directions and foster new multidisciplinary collaborations.
Download or read book Surgical Robotics written by Jacob Rosen and published by Springer Science & Business Media. This book was released on 2011-01-15 with total page 827 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surgical robotics is a rapidly evolving field. With roots in academic research, surgical robotic systems are now clinically used across a wide spectrum of surgical procedures. Surgical Robotics: Systems Applications and Visions provides a comprehensive view of the field both from the research and clinical perspectives. This volume takes a look at surgical robotics from four different perspectives, addressing vision, systems, engineering development and clinical applications of these technologies. The book also: -Discusses specific surgical applications of robotics that have already been deployed in operating rooms -Covers specific engineering breakthroughs that have occurred in surgical robotics -Details surgical robotic applications in specific disciplines of surgery including orthopedics, urology, cardiac surgery, neurosurgery, ophthalmology, pediatric surgery and general surgery Surgical Robotics: Systems Applications and Visions is an ideal volume for researchers and engineers working in biomedical engineering.
Book Synopsis Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice by : Daniel A. Hashimoto
Download or read book Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice written by Daniel A. Hashimoto and published by McGraw Hill Professional. This book was released on 2021-03-08 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a solid foundation in surgical AI with this engaging, comprehensive guide for AI novices Machine learning, neural networks, and computer vision in surgical education, practice, and research will soon be de rigueur. Written for surgeons without a background in math or computer science, Artificial Intelligence in Surgery provides everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice. Comprehensive and easy to understand, this first-of-its-kind resource illustrates the use of AI in surgery through real-life examples. It covers the issues most relevant to your practice, including: Neural Networks and Deep Learning Natural Language Processing Computer Vision Surgical Education and Simulation Preoperative Risk Stratification Intraoperative Video Analysis OR Black Box and Tracking of Intraoperative Events Artificial Intelligence and Robotic Surgery Natural Language Processing for Clinical Documentation Leveraging Artificial Intelligence in the EMR Ethical Implications of Artificial Intelligence in Surgery Artificial Intelligence and Health Policy Assessing Strengths and Weaknesses of Artificial Intelligence Research Finally, the appendix includes a detailed glossary of terms and important learning resources and techniques―all of which helps you interpret claims made by studies or companies using AI.
