Towards Standardized Acquisition with a Dual-probe Ultrasound Robot for Fetal Imaging

Wellcome Trust IEH Awar

Development and Validation of a Three-Dimensional Optical Imaging System for Chest Wall Deformity Measurement

Congenital chest wall deformities (CWD) are malformations of the thoracic cage that become more pronounced during early adolescence. Pectus excavatum (PE) is the most common CWD, characterized by an inward depression of the sternum and adjacent costal cartilage. A cross-sectional computed tomography (CT) image is mainly used to calculate the chest thoracic indices. Physicians use the indices to quantify PE deformity, prescribe surgical or non-surgical therapies, and evaluate treatment outcomes. However, the use of CT is increasingly causing physicians to be concerned about the radiation doses administered to young patients. Furthermore, radiographic indices are an unsafe and expensive method of evaluating non-surgical treatments involving gradual chest wall changes. Flexible tape or a dowel-shaped ruler can be used to measure changes on the anterior side of the thorax; however, these methods are subjective, prone to human error, and cannot accurately measure small changes. This study aims to fill this gap by exploring three-dimensional optical imaging techniques to capture patients’ chest surfaces. The dissertation describes the development and validation of a cost-effective and safe method for objectively evaluating treatment progress in children with chest deformities. First, a study was conducted to evaluate the performance of low-cost 3D scanning technologies in measuring the severity of CWD. Second, a multitemporal surface mesh registration pipeline was developed for aligning 3D torso scans taken at different clinical appointments. Surface deviations were assessed between closely aligned scans. Optical indices were calculated without exposing patients to ionizing radiation, and changes in chest shape were visualized on a color-coded heat map. Additionally, a statistical model of chest shape built from healthy subjects was proposed to assess progress toward normal chest and aesthetic outcomes. The system was validated with 3D and CT datasets from a multi-institutional cohort. The findings indicate that optical scans can detect differences on a millimeter scale, and optical indices can be applied to approximate radiographic indices. In addition to improving patient awareness, visual representations of changes during nonsurgical treatment can enhance patient compliance

Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi

Acquisition and reconstruction of 3D objects for robotic machining

With the evolution of the techniques of acquisition of Three-Dimensional (3D) image it became possible to apply these in more and more areas, as well as to be used for research and hobbyists due to the appearance of low cost 3D scanners. Among the application of 3D acquisitions is the reconstruction of objects, which allows for example to redo or remodel an existing object that is no longer on the market. Another rise tech is industrial robot, that is highly present in the industry and can perform several tasks, even machining activities, and can be applied in more than one type of operation. The purpose of this work is to acquire a 3D scene with low-cost scanners and use this acquisition to create the tool path for roughing a workpiece, using an industrial robot for this machining task. For the acquisition, the Skanect software was used, which had satisfactory results for the work, and the exported file of the acquisition was worked on the MeshLab and Meshmixer software, which were used to obtain only the interest part for the milling process. With the defined work object, it was applied in Computer Aided Manufacturing (CAM) software, Fusion 360, to generate the tool path for thinning in G-code, which was converted by the RoboDK software to robot code, and this also allowed to make simulation of the machining with the desired robot. With the simulation taking place as expected, it was implemented in practice, performing the 3D acquisition machining, thus being able to verify the machining technique used. Furthermore, with the results of acquire, generation of toolpath and machining, was possible to validate the proposed solution and reach a conclusion of possible improvements for this project.Com a evolução das técnicas de aquisição de imagem 3D tornou-se possível aplicá-las em cada vez mais áreas, bem como serem utilizadas por pesquisadores e amadores devido ao surgimento de scanners 3D de baixo custo. Entre as aplicações de aquisições 3D está a reconstrução de objetos, o que permite, por exemplo, refazer ou remodelar um objeto existente que não está mais no mercado. Outra tecnologia em ascensão é o robô industrial, que está muito presente na indústria e pode realizar diversas tarefas, até mesmo atividades de fabrico, e ser aplicado em mais de um tipo de operação. O objetivo deste trabalho é adquirir uma cena 3D com scanners de baixo custo e utilizar esta aquisição para criar o caminho da ferramenta para o desbaste de uma peça, utilizando um robô industrial nesta tarefa de usinagem. Para a aquisição foi utilizado o software Skanect, que obteve resultados satisfatórios para o trabalho, e o arquivo exportado da aquisição foi trabalhado nos softwares MeshLab e Meshmixer, os quais foram utilizados para obter apenas a parte de interesse para o processo de fresagem. Com o objeto de trabalho defino, este foi aplicado em software CAM, Fusion 360, para gerar o caminho de ferramentas para o desbaste em G-code, o qual foi convertido pelo Software RoboDK para código de rôbo, e este também permitiu fazer simulação da maquinação com o rôbo pretendido. Com a simulação ocorrendo de acordo com o esperado, esta foi implementada em prática, realizando a maquinação da aquisição 3D, assim podendo verificar a técnica de maquinação utilizada. Além disso com os resultados de aquisição, geração de toolpath e maquinação, foi possível validar a solução proposta e chegar a uma conclusão de possíveis melhorias para este projeto

Robot-Assisted Image-Guided Interventions

Image guidance is a common methodology of minimally invasive procedures. Depending on the type of intervention, various imaging modalities are available. Common imaging modalities are computed tomography, magnetic resonance tomography, and ultrasound. Robotic systems have been developed to enable and improve the procedures using these imaging techniques. Spatial and technological constraints limit the development of versatile robotic systems. This paper offers a brief overview of the developments of robotic systems for image-guided interventions since 2015 and includes samples of our current research in this field

Robot-Assisted Image-Guided Interventions

Image guidance is a common methodology of minimally invasive procedures. Depending on the type of intervention, various imaging modalities are available. Common imaging modalities are computed tomography, magnetic resonance tomography, and ultrasound. Robotic systems have been developed to enable and improve the procedures using these imaging techniques. Spatial and technological constraints limit the development of versatile robotic systems. This paper offers a brief overview of the developments of robotic systems for image-guided interventions since 2015 and includes samples of our current research in this field

Personalised Procedures for Thoracic Radiotherapy

This thesis presents the investigation, development, and estimation of two personalised procedures for thoracic cancer therapy in Shenzhen, China and two projects were carried out: (1) respiratory motion management of a lung tumour, and (2) the application of a three-dimensional (3D) printing technique for postmastectomy irradiation. For the first project, all subjects attended sessions of free-breathing (FB) and personalised vocal coaching (VC) for respiratory regulation. Thoracic and abdominal breathing signals were extracted from the subjects’ surface area then estimated as kernel density estimation (KDE) for motion visualisation. The mutual information (MI) and correlation coefficient (CC) calculated from KDEs indicate the variation in the relationship between the two signals. From the 1D signal, through VC, the variation of cycle time and the signal value of end-of-exhale/inhale increased in the patient group but decreased in volunteers. Mixed results were presented on KDE and MI. Compared with FB, VC improves movement consistency between the two signals in eight of eleven subjects by increasing MI. The fixed instruction method showed no improvement for day-to-day variation, while the daily generated instruction enhanced the respiratory regularity in three of five volunteers. VC addresses the variation of the single signal, while the outcome of the two signals, thoracic and abdominal signals, requires further interpretation. The second project aims to address both the enhancement of the skin dose and avoidance of hotspots of critical organs, focusing on improving irradiative treatment for post-mastectomy patients. A 3D-printed bolus was presented as a solution for the air gap between the bolus and skin. The results showed no evidence of significant skin dose enhancement with the printed bolus. Additionally, an air gap larger than 5 mm was evident in all patients. Until a solution for complete bolus adhesion is found, this customised bolus is not suitable for clinical use

Autonomous 3D mapping and surveillance of mines with MAVs

A dissertation Submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, for the degree of Master of Science. 12 July 2017.The mapping of mines, both operational and abandoned, is a long, di cult and occasionally dangerous task especially in the latter case. Recent developments in active and passive consumer grade sensors, as well as quadcopter drones present the opportunity to automate these challenging tasks providing cost and safety bene ts. The goal of this research is to develop an autonomous vision-based mapping system that employs quadrotor drones to explore and map sections of mine tunnels. The system is equipped with inexpensive, structured light, depth cameras in place of traditional laser scanners, making the quadrotor setup more viable to produce in bulk. A modi ed version of Microsoft's Kinect Fusion algorithm is used to construct 3D point clouds in real-time as the agents traverse the scene. Finally, the generated and merged point clouds from the system are compared with those produced by current Lidar scanners.LG201

Mixed Reality system to study deformable objects: Breast Cancer application

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2020-2021. Directors: Eduardo Soudah i Óscar de Coss. Tutor: Aida NiñerolaA significant amount of women who go through a breast cancer conservative surgery to treat early stage breast cancer undergo a repeat surgery due to concerns that residual tumor was left behind. To avoid this, tumor localization is needed to assist the surgeon in order to determine tumor extent and also, it is critical to account for tissue deformations. For these reasons, new navigation systems, like the one proposed on this project, are emerging to cover those needs. This project focuses on the use of a Mixed Reality system to improve the accuracy in placing the static hologram of the tumor and, to implement a dynamical hologram when deformation takes place. In order to do so, two different molds with objects inside have been manufactured. Next, two different approaches were considered, a mathematical approach to create a 3D CAD model of the molds and a medical approach, which consisted in performing a CT and then, segment the images. The models were post-processed and imported to the HoloLens head-mounted display. The system was tested on the molds and on a breast phantom provided by the Hospital Clinic. The results obtained were encouraging and although some things need to be improved, this exciting new use for Augmented Reality has the potential to improve the lives of many patients