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AR-Based Surgical Navigation System Based on dual Plane Calibration and 2d/3d Registration 9

AR-Based Surgical Navigation System Based on Dual Plane Cali...

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9th International conference on virtual Reality, ICVR 2023

作者： Yin, Li Fu, Hang Yang, demin Fan, Xingqi Tu, Puxun Chen, Xiaojun Shanghai Jiao Tong University Institute of Biomedical Manufacturing and Life Quality Engineering School of Mechanical Engineering Shanghai China

ISBN: (纸本)9798350345810

Surgical procedures are often associated with a range of potential risks, including nerve tissue damage resulting from complex lesion structures, narrow surgical spaces, or the low accuracy of the operating surgeon. The rise of augmented reality technology has attracted wide attention in the field of complementary medicine. The safe and low delay augmented-reality assisted surgery system can effectively guide the accurate operation. At the same time, augmented reality technology can make surgical sites more intuitive. In this work, we propose a novel surgical operating system that leverages coordinate system transformation and optical navigation to improve precision and safety. Our approach involves the integration of medical images and optical tracking devices before and during surgery to achieve coordinate transformation between the patient's position, surgical instruments, and the pre-surgery CT scan. This process involves calibration, registration, and other critical procedures. At the same time, the study also introduced the function of augmented reality. doctors wearing augmented reality glasses can use the system to see more vivid scenes of surgery. during the calibration phase, we utilize biplanar and interpolation algorithms to obtain the conversion relationship between the C-arm emission source and the X-ray image coordinate system. In the registration stage, we convert the preoperative 3d CT into a dRR image using digital reconstruction image technology, which we then register with the 2d X-ray during the operation. To optimize the iteration, we employ the improved Powell algorithm. The algorithm demonstrates an average angle and position error of 0.62° and 0.56mm, respectively. Through the transformation of spatial position relationship, the transformation relationship between preoperative CT and intraoperative patient position was obtained. A user-friendly, integrated software system has been developed that allows users to view the relative relationship

关键词： Augmented reality

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11th EAI International conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

11th EAI International Conference on MOBILe Wireless MiddleW...

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11th EAI International conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

ISBN: (纸本)9783031344961

The proceedings contain 23 papers. The special focus in this conference is on MOBILe Wireless MiddleWARE, Operating Systems and Applications. The topics include: design of Aerospace Cloud Computing Server Based on docker Cluster;analysis and Simulation of High Orbit Weak Signal Tracking Algorithm;avionics System architectures for Software-defined Spacecraft;research and Application of Energy Efficiency Optimization Algorithm for Spacecraft Simulation Platform;SAdA: SdN Architecture Based Secure dynamic Access Scheme for Satellite Network;Research on the Concept and Connotation of Space Proving Grounds (SPG);a Multi-agent Based Satellite Health Management System Architecture and Implementation Scheme;avionic System Architecture design of the Manned deep Space Exploration Spacecraft;research on Tianwen-1 Mars Probe Relay Communication Technology;deep Reinforcement Learning Based Congestion Control Mechanism for SdN and NdN in Satellite Networks;design and Practice of Communication System during EdL for Mars Probe;Study on EMC Influence of Zhu Rong Rover UHF Band Communication System;design and Implementation of Power Supply and distribution System for Mars Landing Mission;research on Integrated Operation design of Low Orbit Remote Sensing Satellite for Intelligent Application;intelligent Automated Penetration Testing Using Reinforcement Learning to Improve the Efficiency and Effectiveness of Penetration Testing;time Slot Correlation-Based Caching Strategy for Information-Centric Satellite Networks;design and Implementation of a Pipeline-Based data Scheduling Method for Spacecraft with Multiple data Buses;Research on the development of Intelligent Space System (ISS);features Extraction of reconstruction Model Using in Augmented Reality System of Teleoperation Mobile Robots;research on Rapid 3d reconstruction for Teleoperation in Manned Lunar Exploration Mission.

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SceNeRFlow: Time-Consistent reconstruction of General dynamic Scenes

SceNeRFlow: Time-Consistent Reconstruction of General Dynami...

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International conference on 3d Imaging, Modeling, Processing, visualization and Transmission (3dIMPVT)

作者： Edith Tretschk Vladislav Golyanik Michael Zollhöfer Aljaž Božič Christoph Lassner Christian Theobalt Max Planck Institute for Informatics Saarland Informatics Campus Meta Reality Labs Research

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

Existing methods for the 4d reconstruction of general, non-rigidly deforming objects focus on novel-view synthesis and neglect correspondences. However, time consistency enables advanced downstream tasks like 3d editing, motion analysis, or virtual-asset creation. We propose SceNeRFlow to reconstruct a general, non-rigid scene in a time-consistent manner. Our dynamic-NeRF method takes multi-view RGB videos and background images from static cameras with known camera parameters as input. It then reconstructs the deformations of an estimated canonical model of the geometry and appearance in an online fashion. Since this canonical model is time-invariant, we obtain correspondences even for long-term, long-range motions. We employ neural scene representations to parametrize the components of our method. Like prior dynamic-NeRF methods, we use a backwards deformation model. We find nontrivial adaptations of this model necessary to handle larger motions: We decompose the deformations into a strongly regularized coarse component and a weakly regularized fine component, where the coarse component also extends the deformation field into the space surrounding the object, which enables tracking over time. We show experimentally that, unlike prior work that only handles small motion, our method enables the reconstruction of studio-scale motions.

关键词： deformable models Adaptation models Three-dimensional displays deformation Tracking dynamics Cameras

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An Intelligent Glioma Surgery-Assisted Navigation System Incorporating 3d-ResUNet and Mixed Reality

An Intelligent Glioma Surgery-Assisted Navigation System Inc...

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Image Processing, Computer Vision and Machine Learning (ICICML), International conference on

作者： Yue-Yang Zhong Shu-Yi Wang Yu-Qing Miao Tao Zhang Hao-Liang Li School of Health Science and Engineering University of Shanghai for Science and Technology Shanghai China School of Materials and Chemistry University of Shanghai for Science and Technology Shanghai China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

In this study, we propose an intelligent navigation system for glioma surgery that combines 3d-ResUNet and mixed reality technologies. The aim of this system is to enhance the accuracy and safety of glioma surgery. Automatic segmentation is achieved through the use of multimodal MRI data and the 3d-ResUNet model. Additionally, 3d reconstruction is performed using VTK to enable hierarchical visualization of brain tissues and tumor regions. By utilizing the Vuforia platform and HoloLens 2, the system is able to align and display virtual and real environments in real-time, providing surgeons with efficient surgical navigation support. Experimental results demonstrate that the system exhibits excellent segmentation performance, as indicated by the dice coefficient and Jaccard index. It is anticipated that this system will be adopted and utilized in clinical surgery.

关键词： Solid modeling Image segmentation Three-dimensional displays Accuracy Navigation Computational modeling Surgery Mixed reality Real-time systems Lesions

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A Multi-head Two-level Attention-based Network for Plant-part Segmentation on 3d Point Cloud 10

A Multi-head Two-level Attention-based Network for Plant-par...

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10th International conference on Information Systems and Computing Technology, ISCTech 2022

作者： Luo, Lin Zeng, An Pan, dan School of Computer Science and Technology Guangdong University of Technology Guangzhou China School of Electronics and Information Guangdong Polytechnic Normal University Guangzhou China

ISBN: (纸本)9798350332933

The automated and accurate segmentation of structural plant parts from 3d point cloud has becoming a promising approach for non-destructive and high-throughput measurement of sought-after phenotypic traits in plant phenotyping. However, previous studies towards automatic segmentation of plants relied heavily on environmental circumstances, vulnerability toward occlusion, sensor set-up, hand-crafted features, as well as manually tuned thresholds. The purpose of this study was to establish a complete framework for plant-part segmentation of the point cloud in 3d space. To this end, we built an image capturing system to capture Caladium bicolor images for 3d reconstruction, and then hand-labeled the point cloud data. Furthermore, based on attention mechanism, we proposed a Muti-head Two-level Attention-based Network (MTANet) to hierarchically capture geometric features and predict per-point semantic annotations directly on the basis of the fully labelled point cloud data. The experimental results outperformed other main-stream point-based deep learning architectures with Overall Accuracy (OAcc), mean Accuracy (mAcc), and the mean Intersection over Union (mIoU) reached 98.73%, 94.67% and 92.58%, respectively. In addition, we also conducted ablation experiments to evaluate its efficiency and examine specific decisions of the network design. This study may contribute to automated measurements of plant phenotypic traits in breeding programs. © 2022 IEEE.

关键词： Semantics

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A System for Retargeting Human Motion to Robot with Augmented Feedback via a digital Twin Setup

A System for Retargeting Human Motion to Robot with Augmente...

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International conference on Control, Automation and Robotics (ICCAR)

作者： Jinhhao Ng Chee Kwang Quah Ren Tsong Chua Budianto Tandianus Singapore Institute of Technology Singapore Clemvision Pte Ltd Singapore

ISBN: (数字)9798350373172

ISBN: (纸本)9798350373189

This paper introduces a human-robot-interaction approach for a robot to learn complex automated tasks via natural human actions. Our system comprises of marker-less human pose estimation that is retargeted onto a robot for it to learn for demonstration (Lfd) while incorporating augmented visual feedback to the human. This is done through a digital twin setup comprising of the virtual environment that is a replica of the physical scene with the robot on one end and the human teleoperator on the other. The system begins with a low-cost off-the-shelf marker-less human capture module before its posture is mapped across to the robot via its virtual digital twin. Our mapping takes into account the difference between the human and robot joints by normalization of the Euclidean among the joint lengths. Also, we have included a preliminary adaptive hysteresis thresholding method to overcome potential jittering problem in precision of joint location during motion capture while preserving the high frequency movements. Finally, our system is integrated with state-of-the-art 3d scene reconstruction and object detection methods.

关键词： visualization Teleoperators Three-dimensional displays Pose estimation virtual environments Object detection digital twins

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3d Vessel Segmentation in CT for Augmented and virtual Reality 1st

3D Vessel Segmentation in CT for Augmented and Virtual Reali...

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1st Mediterranean Forum - data Science conference, MeFdATA 2020

作者： Simoni, Agnese Tiribilli, Eleonora Lorenzetto, Cosimo Manetti, Leonardo Iadanza, Ernesto Bocchi, Leonardo Department of Information Engineering University of Florence Via S. Marta 3 Florence50139 Italy Epica Imaginalis Via Rodolfo Morandi 13/15 Sesto Fiorentino50019 Italy

ISBN: (纸本)9783030728045

Blood vessels 3d rendering has numerous applications, ranging from diagnosis to pre-procedural and surgical approaches as it enriches vessels visualization for the clinician. In this paper, we propose a 3d blood vessels segmentation method designed for use with a cone beam computed tomography (CBCT). The algorithm constitutes a module in the development of an angio-CT visualization system, based on augmented or virtual reality as instruments supporting and improving medical decisions. The proposed segmentation tool exploits a bone segmentation step for easing the extraction of blood vessels. Both steps are based on region growing technique. For each subject are used two CBCT acquisitions, where the first one is acquired with a traditional CT scan and is used for bone extraction, while the second one is acquired after contrast medium administration and is used for vessels reconstruction. This novel segmentation algorithm provides an automatic and accurate tool to segment and render blood vessels tree. 3d anatomical models were viewed through a virtual reality environment in order to validate the visualization system. © 2021, Springer Nature Switzerland AG.

关键词： Blood vessels

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Lung infection region quantification, recognition, and virtual reality rendering of CT scan of COVId-19

Lung infection region quantification, recognition, and virtu...

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conference on Multimodal Image Exploitation and Learning

作者： Benbelkacem, Samir Oulefki, Adel Agaian, Sos Trongtirakul, Thaweesak Aouam, djamel Zenati-Henda, Nadia Amara, Kahina Ctr Dev Technol Avancees CDTA POB 17 Algiers 16081 Algeria CUNY Coll Staten Isl Dept Comp Sci 2800 Victory Blvd Staten Isl NY 10314 USA Rajamangala Univ Technol Phra Nakhon Fac Ind Educ 399 Samsen Rd Bangkok 10300 Thailand

ISBN: (数字)9781510643062

ISBN: (纸本)9781510643062

In recent years, virtual reality has experienced steady growth in the medical field, such as surgery, rehabilitation, disease diagnostic, and learning. The 3d representation of radiological images plays a significant role in disease diagnostic and treatment planning compared to standard 2d medical images. Since March 2019, almost all laboratories and medical centers have improved their patients' management methods with confirmed coronavirus (COVId-19) disease. Providing appropriate treatment in the well moment may contribute to save lives. Our study aims to develop an advanced COVId-19 CT scan image segmentation and 3d visualization using an unsupervised thresholding procedure and virtual reality technology to better plan and monitor affected patients. Our proposed system provides three-dimensional COVId-19 lesion visualization, which clearly shows segmented infected region (in 3d) rather than traditional two-dimensional images. Radiologists and doctors on actual patients tested the developed system. The experimenters noticed that VR rendering of CT scan of COVId-19 improves the disease diagnostic and drug prescription.

关键词： virtual Reality 3d reconstruction Segmentation CT Scan COVId-19

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Towards Multi-Angle Multispectral Optical 3d Porometry and Lens-Less Porometry of Civil Engineering Composites and Geocomposites Including Biodegradable Ones 7

Towards Multi-Angle Multispectral Optical 3D Porometry and L...

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7th International Technical conference on Frontiers of Hydraulic and Civil Engineering Technology, HCET 2022

作者： Grigorieva, Elena Gradov, Oleg Gradova, Margaret Maklakova, Irina IBCP RAS Kosygina Str. 4 Moscow119991 Russia FRC CP RAS Kosygina Str. 4 Moscow119991 Russia

ISBN: (纸本)9781643683546

In this work we demonstrate the images of multi-angle porometry of civil engineering composites with the static pores. We also demonstrate an example of the application of multi-angle scanning methods where each pore visualization angle corresponds to the certain time moment. The light source can be either incoherent or coherent, which determines the data interpretation principles and data processing algorithms. The light detector can be either optical microscopic (with lenses) or lens-less, that is, either a microscope with an objective or a lens-less one, especially a holographic lens-less microscope. The latter is by definition compatible with multi-angle microporometry. The data on reconstruction of the surface texture of a complex pore using an incoherent light source and the Sobel-Feldman operator (Stanford Artificial Intelligence Laboratory (SAIL)) is presented. © 2022 The authors and IOS Press.

关键词： Textures

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Shape-prior Free Space-time Neural Radiance Field for 4d Semantic reconstruction of dynamic Scene from Sparse-View RGB Videos

Shape-prior Free Space-time Neural Radiance Field for 4D Sem...

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IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Sandika Biswas Biplab Banerjee Hamid Rezatofighi Indian Institute of Technology Bombay Monash University Faculty of Information Technology Monash University

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Many applications in Augmented/virtual Reality or robotics require precise geometry modeling of individual elements in a dynamic scene under a sparse-view camera setup, without any prior information about their semantic labels or shapes. In our research, we introduce a 3d shape prior-free Neural Radiance Field-based technique for detailed geometry reconstruction under human-object interactions, offering an explicit surface reconstruction with semantic labels for reconstructed geometry. Our approach harnesses the capabilities of an Invertible Neural Network to learn a deformation function that effectively connects local (current-frame input) and canonical spaces for each of the components under motion. The deformation process is guided by temporal constraints from multi-frame, facilitating the precise reconstruction of the complex interactions between humans and objects. Our experimental evaluations highlight the effectiveness of our framework, demonstrating its ability to accurately represent both the comprehensive object-compositional scene and individual components over state-of-the-art methods, under complex interactions between the scene entities. This research is deemed to mark a significant stride in semantic 3d geometry modeling within dynamic interactive environments, relying solely on sparse multi-view RGB data.

关键词： Geometry Training Three-dimensional displays Shape deformation Semantics Neural radiance field Image reconstruction Surface treatment Videos

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