Ultrasound-Augmented Laparoscopy

Laparoscopic surgery is perhaps the most common minimally invasive procedure for many diseases in the abdomen. Since the laparoscopic camera provides only the surface view of the internal organs, in many procedures, surgeons use laparoscopic ultrasound (LUS) to visualize deep-seated surgical targets. Conventionally, the 2D LUS image is visualized in a display spatially separate from that displays the laparoscopic video. Therefore, reasoning about the geometry of hidden targets requires mentally solving the spatial alignment, and resolving the modality differences, which is cognitively very challenging. Moreover, the mental representation of hidden targets in space acquired through such cognitive medication may be error prone, and cause incorrect actions to be performed. To remedy this, advanced visualization strategies are required where the US information is visualized in the context of the laparoscopic video. To this end, efficient computational methods are required to accurately align the US image coordinate system with that centred in the camera, and to render the registered image information in the context of the camera such that surgeons perceive the geometry of hidden targets accurately. In this thesis, such a visualization pipeline is described. A novel method to register US images with a camera centric coordinate system is detailed with an experimental investigation into its accuracy bounds. An improved method to blend US information with the surface view is also presented with an experimental investigation into the accuracy of perception of the target locations in space

EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers

Ultrasound (US) is the most widely used fetal imaging technique. However, US images have limited capture range, and suffer from view dependent artefacts such as acoustic shadows. Compounding of overlapping 3D US acquisitions into a high-resolution volume can extend the field of view and remove image artefacts, which is useful for retrospective analysis including population based studies. However, such volume reconstructions require information about relative transformations between probe positions from which the individual volumes were acquired. In prenatal US scans, the fetus can move independently from the mother, making external trackers such as electromagnetic or optical tracking unable to track the motion between probe position and the moving fetus. We provide a novel methodology for image-based tracking and volume reconstruction by combining recent advances in deep learning and simultaneous localisation and mapping (SLAM). Tracking semantics are established through the use of a Residual 3D U-Net and the output is fed to the SLAM algorithm. As a proof of concept, experiments are conducted on US volumes taken from a whole body fetal phantom, and from the heads of real fetuses. For the fetal head segmentation, we also introduce a novel weak annotation approach to minimise the required manual effort for ground truth annotation. We evaluate our method qualitatively, and quantitatively with respect to tissue discrimination accuracy and tracking robustness.Comment: MICCAI Workshop on Perinatal, Preterm and Paediatric Image analysis (PIPPI), 201

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Advanced Endoscopic Navigation:Surgical Big Data,Methodology,and Applications

随着科学技术的飞速发展，健康与环境问题日益成为人类面临的最重大问题之一。信息科学、计算机技术、电子工程与生物医学工程等学科的综合应用交叉前沿课题，研究现代工程技术方法，探索肿瘤癌症等疾病早期诊断、治疗和康复手段。本论文综述了计算机辅助微创外科手术导航、多模态医疗大数据、方法论及其临床应用：从引入微创外科手术导航概念出发，介绍了医疗大数据的术前与术中多模态医学成像方法、阐述了先进微创外科手术导航的核心流程包括计算解剖模型、术中实时导航方案、三维可视化方法及交互式软件技术，归纳了各类微创外科手术方法的临床应用。同时，重点讨论了全球各种手术导航技术在临床应用中的优缺点，分析了目前手术导航领域内的最新技术方法。在此基础上，提出了微创外科手术方法正向数字化、个性化、精准化、诊疗一体化、机器人化以及高度智能化的发展趋势。【Abstract】Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.X.L. acknowledges funding from the Fundamental Research Funds for the Central Universities. T.M.P. acknowledges funding from the Canadian Foundation for Innovation, the Canadian Institutes for Health Research, the National Sciences and Engineering Research Council of Canada, and a grant from Intuitive Surgical Inc

Registration of ultrasound and computed tomography for guidance of laparoscopic liver surgery

Laparoscopic Ultrasound (LUS) imaging is a standard tool used for image-guidance during laparoscopic liver resection, as it provides real-time information on the internal structure of the liver. However, LUS probes are di cult to handle and their resulting images hard to interpret. Additionally, some anatomical targets such as tumours are not always visible, making the LUS guidance less e ective. To solve this problem, registration between the LUS images and a pre-operative Computed Tomography (CT) scan using information from blood vessels has been previously proposed. By merging these two modalities, the relative position between the LUS images and the anatomy of CT is obtained and both can be used to guide the surgeon. The problem of LUS to CT registration is specially challenging, as besides being a multi-modal registration, the eld of view of LUS is signi cantly smaller than that of CT. Therefore, this problem becomes poorly constrained and typically an accurate initialisation is needed. Also, the liver is highly deformed during laparoscopy, complicating the problem further. So far, the methods presented in the literature are not clinically feasible as they depend on manually set correspondences between both images. In this thesis, a solution for this registration problem that may be more transferable to the clinic is proposed. Firstly, traditional registration approaches comprised of manual initialisation and optimisation of a cost function are studied. Secondly, it is demonstrated that a globally optimal registration without a manual initialisation is possible. Finally, a new globally optimal solution that does not require commonly used tracking technologies is proposed and validated. The resulting approach provides clinical value as it does not require manual interaction in the operating room or tracking devices. Furthermore, the proposed method could potentially be applied to other image-guidance problems that require registration between ultrasound and a pre-operative scan

Evaluation of a calibration rig for stereo laparoscopes

BACKGROUND: Accurate camera and hand-eye calibration are essential to ensure high quality results in image guided surgery applications. The process must also be able to be undertaken by a non-expert user in a surgical setting. PURPOSE: This work seeks to identify a suitable method for tracked stereo laparoscope calibration within theatre. METHODS: A custom calibration rig, to enable rapid calibration in a surgical setting, was designed. The rig was compared against freehand calibration. Stereo reprojection, stereo reconstruction, tracked stereo reprojection and tracked stereo reconstruction error metrics were used to evaluate calibration quality. RESULTS: Use of the calibration rig reduced mean errors: reprojection (1.47mm [SD 0.13] vs 3.14mm [SD 2.11], p-value 1e-8), reconstruction (1.37px [SD 0.10] vs 10.10px [SD 4.54], p-value 6e-7) and tracked reconstruction (1.38mm [SD 0.10] vs 12.64mm [SD 4.34], p-value 1e-6) compared with freehand calibration. The use of a ChArUco pattern yielded slightly lower reprojection errors, while a dot grid produced lower reconstruction errors and was more robust under strong global illumination. CONCLUSION: The use of the calibration rig results in a statistically significant decrease in calibration error metrics, versus freehand calibration, and represents the preferred approach for use in the operating theatre. This article is protected by copyright. All rights reserved

Ultrasound 3D reconstruction of malignant masses in robotic-assisted partial nephrectomy using the PAF rail system: a comparison study

PURPOSE: In robotic-assisted partial nephrectomy (RAPN), the use of intraoperative ultrasound (IOUS) helps to localise and outline the tumours as well as the blood vessels within the kidney. The aim of this work is to evaluate the use of the pneumatically attachable flexible (PAF) rail system for US 3D reconstruction of malignant masses in RAPN. The PAF rail system is a novel device developed and previously presented by the authors to enable track-guided US scanning. METHODS: We present a comparison study between US 3D reconstruction of masses based on: the da Vinci Surgical System kinematics, single- and stereo-camera tracking of visual markers embedded on the probe. An US-realistic kidney phantom embedding a mass is used for testing. A new design for the US probe attachment to enhance the performance of the kinematic approach is presented. A feature extraction algorithm is proposed to detect the margins of the targeted mass in US images. RESULTS: To evaluate the performance of the investigated approaches the resulting 3D reconstructions have been compared to a CT scan of the phantom. The data collected indicates that single camera reconstruction outperformed the other approaches, reconstructing with a sub-millimetre accuracy the targeted mass. CONCLUSIONS: This work demonstrates that the PAF rail system provides a reliable platform to enable accurate US 3D reconstruction of masses in RAPN procedures. The proposed system has also the potential to be employed in other surgical procedures such as hepatectomy or laparoscopic liver resection

Image guided robotic assistance for the diagnosis and treatment of tumor

The aim of this thesis is to demonstrate the feasibility and the potentiality of introduction of robotics and image guidance in the overall oncologic workflow, from the diagnosis to the treatment phase. The popularity of robotics in the operating room has grown in recent years. Currently the most popular systems is the da Vinci telemanipulator (Intuitive Surgical), it is based on a master-slave control, for minimally invasive surgery and it is used in several surgical fields such us urology, general, gynecology, cardiothoracic. An accurate study of this system, from a technological field of view, has been conducted addressing all drawbacks and advantages of this system. The da Vinci System creates an immersive operating environment for the surgeon by providing both high quality stereo visualization and a human-machine interface that directly connects the surgeon’s hands to the motion of the surgical tool tips inside the patient’s body. It has undoubted advantages for the surgeon work and for the patient health, at least for some interventions, while its very high costs leaves many doubts on its price benefit ratio. In the robotic surgery field many researchers are working on the optimization and miniaturization robots mechanic, while others are trying to obtain smart functionalities to realize robotic systems, that, “knowing” the patient anatomy from radiological images, can assists the surgeon in an active way. Regarding the second point, image guided systems can be useful to plan and to control medical robots motion and to provide the surgeon pre-operative and intra-operative images with augmented reality visualization to enhance his/her perceptual capacities and, as a consequence, to improve the quality of treatments. To demonstrate this thesis some prototypes has been designed, implemented and tested. The development of image guided medical devices, comprehensive of augmented reality, virtual navigation and robotic surgical features, requires to address several problems. The first ones are the choosing of the robotic platform and of the image source to employ. An industrial anthropomorphic arm has been used as testing platform. The idea of integrating industrial robot components in the clinical workflow has been supported by the da Vinci technical analysis. The algorithms and methods developed, regarding in particular robot calibration, based on literature theories and on an easily integration in the clinical scenario, can be adapted to each anthropomorphic arm. In this way this work can be integrated with light-weight robots, for industrial or clinical use, able to work in close contact to humans, which will become numerous in the early future. Regarding the medical image source, it has been decided to work with ultrasound imaging. Two-dimensional ultrasound imaging is widely used in clinical practice because is not dangerous for the patient, inexpensive, compact and it is a highly flexible imaging that allows users to study many anatomic structures. It is routinely used for diagnosis and as guidance in percutaneous treatments. However the use of 2D ultrasound imaging presents some disadvantages that require great ability of the user: it requires that the clinician mentally integrates many images to reconstruct a complete idea of the anatomy in 3D. Furthermore the freehand control of the probe make it difficult to individuate anatomic positions and orientations and probe repositioning to reach a particular location. To overcome these problems it has been developed an image guided system that fuse 2D US real time images with routinely CT or MRI 3D images, previously acquired from the patient, to enhance clinician orientation and probe guidance. The implemented algorithms for robot calibration and US image guidance has been used to realize two applications responding to specific clinical needs. The first one to speed up the execution of routinely and very recurrently procedures like percutaneous biopsy or ablation. The second one to improve a new completely non invasive type of treatment for solid tumors, the HIFU (High Intensity Focused Ultrasound). An ultrasound guided robotic system has been developed to assist the clinician to execute complicated biopsies, or percutaneous ablations, in particular for deep abdominal organs. It was developed an integrated system that provides the clinician two types of assistance: a mixed reality visualization allows accurate and easy planning of needle trajectory and target reaching verification; the robot arm equipped with a six-degree-of-freedom force sensor allows the precise positioning of the needle holder and allows the clinician to adjust, by means of a cooperative control, the planned trajectory to overcome needle deflection and target motion. The second application consists in an augmented reality navigation system for HIFU treatment. HIFU represents a completely non invasive method for treatment of solid tumors, hemostasis and other vascular features in human tissues. The technology for HIFU treatments is still evolving and the systems available on the market have some limitations and drawbacks. A disadvantage resulting from our experience with the machinery available in our hospital (JC200 therapeutic system Haifu (HIFU) by Tech Co., Ltd, Chongqing), which is similar to other analogous machines, is the long time required to perform the procedure due to the difficulty to find the target, using the remote motion of an ultrasound probe under the patient. This problem has been addressed developing an augmented reality navigation system to enhance US guidance during HIFU treatments allowing an easy target localization. The system was implemented using an additional free hand ultrasound probe coupled with a localizer and CT fused imaging. It offers a simple and an economic solution to an easy HIFU target localization. This thesis demonstrates the utility and usability of robots for diagnosis and treatment of the tumor, in particular the combination of automatic positioning and cooperative control allows the surgeon and the robot to work in synergy. Further the work demonstrates the feasibility and the potentiality of the use of a mixed reality navigation system to facilitate the target localization and consequently to reduce the times of sittings, to increase the number of possible diagnosis/treatments and to decrease the risk of potential errors. The proposed solutions for the integration of robotics and image guidance in the overall oncologic workflow, take into account current available technologies, traditional clinical procedures and cost minimization

Augmented reality technology in image-guided therapy: State-of-the-art review.

Image-guided therapies have been on the rise in recent years as they can achieve higher accuracy and are less invasive than traditional methods. By combining augmented reality technology with image-guided therapy, more organs, and tissues can be observed by surgeons to improve surgical accuracy. In this review, 233 publications (dated from 2015 to 2020) on the design and application of augmented reality-based systems for image-guided therapy, including both research prototypes and commercial products, were considered for review. Based on their functions and applications. Sixteen studies were selected. The engineering specifications and applications were analyzed and summarized for each study. Finally, future directions and existing challenges in the field were summarized and discussed