Spatial calibration of an optical see-through head-mounted display

We present here a method for calibrating an optical see-through Head Mounted Display (HMD) using techniques usually applied to camera calibration (photogrammetry). Using a camera placed inside the HMD to take pictures simultaneously of a tracked object and features in the HMD display, we could exploit established camera calibration techniques to recover both the intrinsic and extrinsic properties of the~HMD (width, height, focal length, optic centre and principal ray of the display). Our method gives low re-projection errors and, unlike existing methods, involves no time-consuming and error-prone human measurements, nor any prior estimates about the HMD geometry

A tracker alignment framework for augmented reality

To achieve accurate registration, the transformations which locate the tracking system components with respect to the environment must be known. These transformations relate the base of the tracking system to the virtual world and the tracking system's sensor to the graphics display. In this paper we present a unified, general calibration method for calculating these transformations. A user is asked to align the display with objects in the real world. Using this method, the sensor to display and tracker base to world transformations can be determined with as few as three measurements

An automated calibration method for non-see-through head mounted displays

Accurate calibration of a head mounted display (HMD) is essential both for research on the visual system and for realistic interaction with virtual objects. Yet, existing calibration methods are time consuming and depend on human judgements, making them error prone, and are often limited to optical see-through HMDs. Building on our existing approach to HMD calibration Gilson et al. (2008), we show here how it is possible to calibrate a non-see-through HMD. A camera is placed inside a HMD displaying an image of a regular grid, which is captured by the camera. The HMD is then removed and the camera, which remains fixed in position, is used to capture images of a tracked calibration object in multiple positions. The centroids of the markers on the calibration object are recovered and their locations re-expressed in relation to the HMD grid. This allows established camera calibration techniques to be used to recover estimates of the HMD display's intrinsic parameters (width, height, focal length) and extrinsic parameters (optic centre and orientation of the principal ray). We calibrated a HMD in this manner and report the magnitude of the errors between real image features and reprojected features. Our calibration method produces low reprojection errors without the need for error-prone human judgements

Augmented reality for computer assisted orthopaedic surgery

In recent years, computer-assistance and robotics have established their presence in operating theatres and found success in orthopaedic procedures. Benefits of computer assisted orthopaedic surgery (CAOS) have been thoroughly explored in research, finding improvements in clinical outcomes, through increased control and precision over surgical actions. However, human-computer interaction in CAOS remains an evolving field, through emerging display technologies including augmented reality (AR) – a fused view of the real environment with virtual, computer-generated holograms. Interactions between clinicians and patient-specific data generated during CAOS are limited to basic 2D interactions on touchscreen monitors, potentially creating clutter and cognitive challenges in surgery. Work described in this thesis sought to explore the benefits of AR in CAOS through: an integration between commercially available AR and CAOS systems, creating a novel AR-centric surgical workflow to support various tasks of computer-assisted knee arthroplasty, and three pre–clinical studies exploring the impact of the new AR workflow on both existing and newly proposed quantitative and qualitative performance metrics. Early research focused on cloning the (2D) user-interface of an existing CAOS system onto a virtual AR screen and investigating any resulting impacts on usability and performance. An infrared-based registration system is also presented, describing a protocol for calibrating commercial AR headsets with optical trackers, calculating a spatial transformation between surgical and holographic coordinate frames. The main contribution of this thesis is a novel AR workflow designed to support computer-assisted patellofemoral arthroplasty. The reported workflow provided 3D in-situ holographic guidance for CAOS tasks including patient registration, pre-operative planning, and assisted-cutting. Pre-clinical experimental validation on a commercial system (NAVIO®, Smith & Nephew) for these contributions demonstrates encouraging early-stage results showing successful deployment of AR to CAOS systems, and promising indications that AR can enhance the clinician’s interactions in the future. The thesis concludes with a summary of achievements, corresponding limitations and future research opportunities.Open Acces

The Effectiveness of Monitor-Based Augmented Reality Paradigms for Learning Space-Related Technical Tasks

Currently today there are many types of media that can help individuals learn and excel in the on going effort to acquire knowledge for a specific trait or function in a workplace, laboratory, or learning facility. Technology has advanced in the fields of transportation, information gathering, and education. The need for better recall of information is in demand in a wide variety of areas. Augmented reality (AR) is a technology that may help meet this demand. AR is a hybrid of reality and virtual reality (VR) that uses the three-dimensional location viewed through a video or optical see-through media to capture the object\u27s coordinates and add virtual images, objects, or text superimposed on the scene (Azuma, 1997). The purpose of this research is to investigate four different modes of presentation and the effect of those modes on learning and recall of information using monitor-based Augmented Reality. The four modes of presentation are Select, Observe, Interact and Print modes. Each mode possesses different attributes that may affect learning and recall. The Select mode can be described as a mode of presentation that allows movement of the work piece in front of the tracking camera. The Observe mode involves information presentation using a pre-recorded video scene presented with no interaction with the work piece. The Interact mode allows the user to view a pre-recorded video scene that allows the user to point and click on the component of the work piece with a computer mouse on the monitor. The Print mode consists of printed material of each work piece component. It was hypothesized that the Select mode would provide the user with the richest presentation of information due to information access capabilities helping to decrease work time, reduce the amount of error likelihood during usage, enhance the user\u27s motivation for learning tasks, and increase concurrent learning and performances due to recall and retention. It was predicted that the Select mode would result in trainees that would recall the greatest amount of information even after extended periods of time had elapsed. This hypothesis was not supported. No significant differences between the four groups were found

Bio-Inspired Multi-Spectral Image Sensor and Augmented Reality Display for Near-Infrared Fluorescence Image-Guided Surgery

Background: Cancer remains a major public health problem worldwide and poses a huge economic burden. Near-infrared (NIR) fluorescence image-guided surgery (IGS) utilizes molecular markers and imaging instruments to identify and locate tumors during surgical resection. Unfortunately, current state-of-the-art NIR fluorescence imaging systems are bulky, costly, and lack both fluorescence sensitivity under surgical illumination and co-registration accuracy between multimodal images. Additionally, the monitor-based display units are disruptive to the surgical workflow and are suboptimal at indicating the 3-dimensional position of labeled tumors. These major obstacles have prevented the wide acceptance of NIR fluorescence imaging as the standard of care for cancer surgery. The goal of this dissertation is to enhance cancer treatment by developing novel image sensors and presenting the information using holographic augmented reality (AR) display to the physician in intraoperative settings. Method: By mimicking the visual system of the Morpho butterfly, several single-chip, color-NIR fluorescence image sensors and systems were developed with CMOS technologies and pixelated interference filters. Using a holographic AR goggle platform, an NIR fluorescence IGS display system was developed. Optoelectronic evaluation was performed on the prototypes to evaluate the performance of each component, and small animal models and large animal models were used to verify the overall effectiveness of the integrated systems at cancer detection. Result: The single-chip bio-inspired multispectral logarithmic image sensor I developed has better main performance indicators than the state-of-the-art NIR fluorescence imaging instruments. The image sensors achieve up to 140 dB dynamic range. The sensitivity under surgical illumination achieves 6108 V/(mW/cm2), which is up to 25 times higher. The signal-to-noise ratio is up to 56 dB, which is 11 dB greater. These enable high sensitivity fluorescence imaging under surgical illumination. The pixelated interference filters enable temperature-independent co-registration accuracy between multimodal images. Pre-clinical trials with small animal model demonstrate that the sensor can achieve up to 95% sensitivity and 94% specificity with tumor-targeted NIR molecular probes. The holographic AR goggle provides the physician with a non-disruptive 3-dimensional display in the clinical setup. This is the first display system that co-registers a virtual image with human eyes and allows video rate image transmission. The imaging system is tested in the veterinary science operating room on canine patients with naturally occurring cancers. In addition, a time domain pulse-width-modulation address-event-representation multispectral image sensor and a handheld multispectral camera prototype are developed. Conclusion: The major problems of current state-of-the-art NIR fluorescence imaging systems are successfully solved. Due to enhanced performance and user experience, the bio-inspired sensors and augmented reality display system will give medical care providers much needed technology to enable more accurate value-based healthcare

Intraoperative Planning and Execution of Arbitrary Orthopedic Interventions Using Handheld Robotics and Augmented Reality

The focus of this work is a generic, intraoperative and image-free planning and execution application for arbitrary orthopedic interventions using a novel handheld robotic device and optical see-through glasses (AR). This medical CAD application enables the surgeon to intraoperatively plan the intervention directly on the patient’s bone. The glasses and all the other instruments are accurately calibrated using new techniques. Several interventions show the effectiveness of this approach

From Sensor to Observation Web with Environmental Enablers in the Future Internet

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

Towards markerless orthopaedic navigation with intuitive Optical See-through Head-mounted displays

The potential of image-guided orthopaedic navigation to improve surgical outcomes has been well-recognised during the last two decades. According to the tracked pose of target bone, the anatomical information and preoperative plans are updated and displayed to surgeons, so that they can follow the guidance to reach the goal with higher accuracy, efficiency and reproducibility. Despite their success, current orthopaedic navigation systems have two main limitations: for target tracking, artificial markers have to be drilled into the bone and calibrated manually to the bone, which introduces the risk of additional harm to patients and increases operating complexity; for guidance visualisation, surgeons have to shift their attention from the patient to an external 2D monitor, which is disruptive and can be mentally stressful. Motivated by these limitations, this thesis explores the development of an intuitive, compact and reliable navigation system for orthopaedic surgery. To this end, conventional marker-based tracking is replaced by a novel markerless tracking algorithm, and the 2D display is replaced by a 3D holographic Optical see-through (OST) Head-mounted display (HMD) precisely calibrated to a user's perspective. Our markerless tracking, facilitated by a commercial RGBD camera, is achieved through deep learning-based bone segmentation followed by real-time pose registration. For robust segmentation, a new network is designed and efficiently augmented by a synthetic dataset. Our segmentation network outperforms the state-of-the-art regarding occlusion-robustness, device-agnostic behaviour, and target generalisability. For reliable pose registration, a novel Bounded Iterative Closest Point (BICP) workflow is proposed. The improved markerless tracking can achieve a clinically acceptable error of 0.95 deg and 2.17 mm according to a phantom test. OST displays allow ubiquitous enrichment of perceived real world with contextually blended virtual aids through semi-transparent glasses. They have been recognised as a suitable visual tool for surgical assistance, since they do not hinder the surgeon's natural eyesight and require no attention shift or perspective conversion. The OST calibration is crucial to ensure locational-coherent surgical guidance. Current calibration methods are either human error-prone or hardly applicable to commercial devices. To this end, we propose an offline camera-based calibration method that is highly accurate yet easy to implement in commercial products, and an online alignment-based refinement that is user-centric and robust against user error. The proposed methods are proven to be superior to other similar State-of- the-art (SOTA)s regarding calibration convenience and display accuracy. Motivated by the ambition to develop the world's first markerless OST navigation system, we integrated the developed markerless tracking and calibration scheme into a complete navigation workflow designed for femur drilling tasks during knee replacement surgery. We verify the usability of our designed OST system with an experienced orthopaedic surgeon by a cadaver study. Our test validates the potential of the proposed markerless navigation system for surgical assistance, although further improvement is required for clinical acceptance.Open Acces