Vision Algorithm for the Solar Aspect System of the HEROES Mission

This work covers the design and test of a machine vision algorithm for generating high-accuracy pitch and yaw pointing solutions relative to the sun for the High Energy Replicated Optics to Explore the Sun (HEROES) mission. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small fiducial markers. Images of this plate were processed in real time to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an "Average Intersection" method, fiducial detection by a matched filter approach, identification with an ad-hoc method based on the spacing between fiducials, and image registration with a simple least squares fit. Performance is verified on a combination of artificially generated images, test data recorded on the ground, and images from the 2013 fligh

Robotic-assisted internal fixation of hip fractures: a fluoroscopy-based intraoperative registration technique

The internal fixation of proximal femoral (hip) fractures is the most frequently performed orthopaedic surgery procedure. When using a sliding compression hip screw, a commonly used fixation device, accurate positioning of the device within the femoral neck-head is achieved by initially drilling a pilot hole. A cannulated component of the hip screw is then inserted over the guide wire (surgical drill bit), which is used to drill the pilot hole. However, in practice, this fluoroscopically controlled drilling process is severely complicated by a depth perception problem and, as such, a surgeon can require several attempts to achieve a satisfactory guide wire placement. A prototype robotic-assisted orthopaedic surgery system has therefore been developed, with a view to achieving accurate right-first-time guide wire insertions. This paper describes the non-invasive digital X-ray photogrammetry-based registration technique which supports the proposed robotic-assisted drilling scenario. Results from preliminary laboratory (in vitro) trials employing this registration technique indicate that the cumulative error associated with the entire X-ray guided robotic system is within acceptable limits for the guide wire insertion process

PROCESSING OF IMAGES IN PASSIVE MARKER BASED MOTION ANALYSIS

The majority of non-contacting motion analysers process images of CCD cameras. Hardware based feature extraction can be utilised to alleviate the necessary computation: markers are attached to the landmark points of the moving objects and the marker images are separated from the environment based on their high luminosity. Data reduction can be achieved by characterising the extracted marker images with the co-ordinates of a single point. When a spherical marker is used then the centre point of its image must be determined. Real-time motion analysers usually can afford simple data processing only. This explains that a simple geometric centroid calculation of binarised images is so popular. The height and width of the marker images are used to characterise image distortion: these measures of ideal circular images are equal. This paper summarises the results of our theoretical research work. For the centre estimation of binarised images a new method with high accuracy, the ring fitting is recommended. Two methods are shown for the processing of distorted images. Both methods can recognise if a distorted image derives from the overlapping of two (or more) marker images. Furthermore, the methods give good estimates of the centres of the individual marker images. The features of multiple level thresholding for the video/digital conversion has also been studied. The results show that the achievable accuracy does not increase proportionally with the increase in resolution

Development of a Three-Dimensional Image-Guided Needle Positioning System for Small Animal Interventions

Conventional needle positioning techniques for small animal microinjections are fraught with issues of repeatability and targeting accuracy. To improve the outcomes of these interventions a small animal needle positioning system guided by micro-computed tomography (micro-CT) imaging was developed. A phantom was developed to calibrate the geometric accuracy of micro-CT scanners to a traceable standard of measurement. Use of the phantom ensures the geometric fidelity of micro-CT images for use in image-guided interventions or other demanding quantitative applications. The design of a robot is described which features a remote center of motion architecture and is compact enough to operate within a micro-CT bore. Methods to calibrate the robot and register it to a micro-CT scanner are introduced. The performance of the robot is characterized and a mean targeting accuracy of 149 ± 41 µm estimated. The robot is finally demonstrated by completing an in vivo biomedical application

Sub-pixel Registration In Computational Imaging And Applications To Enhancement Of Maxillofacial Ct Data

In computational imaging, data acquired by sampling the same scene or object at different times or from different orientations result in images in different coordinate systems. Registration is a crucial step in order to be able to compare, integrate and fuse the data obtained from different measurements. Tomography is the method of imaging a single plane or slice of an object. A Computed Tomography (CT) scan, also known as a CAT scan (Computed Axial Tomography scan), is a Helical Tomography, which traditionally produces a 2D image of the structures in a thin section of the body. It uses X-ray, which is ionizing radiation. Although the actual dose is typically low, repeated scans should be limited. In dentistry, implant dentistry in specific, there is a need for 3D visualization of internal anatomy. The internal visualization is mainly based on CT scanning technologies. The most important technological advancement which dramatically enhanced the clinician\u27s ability to diagnose, treat, and plan dental implants has been the CT scan. Advanced 3D modeling and visualization techniques permit highly refined and accurate assessment of the CT scan data. However, in addition to imperfections of the instrument and the imaging process, it is not uncommon to encounter other unwanted artifacts in the form of bright regions, flares and erroneous pixels due to dental bridges, metal braces, etc. Currently, removing and cleaning up the data from acquisition backscattering imperfections and unwanted artifacts is performed manually, which is as good as the experience level of the technician. On the other hand the process is error prone, since the editing process needs to be performed image by image. We address some of these issues by proposing novel registration methods and using stonecast models of patient\u27s dental imprint as reference ground truth data. Stone-cast models were originally used by dentists to make complete or partial dentures. The CT scan of such stone-cast models can be used to automatically guide the cleaning of patients\u27 CT scans from defects or unwanted artifacts, and also as an automatic segmentation system for the outliers of the CT scan data without use of stone-cast models. Segmented data is subsequently used to clean the data from artifacts using a new proposed 3D inpainting approach

Intraoperative Endoscopic Augmented Reality in Third Ventriculostomy

In neurosurgery, as a result of the brain-shift, the preoperative patient models used as a intraoperative reference change. A meaningful use of the preoperative virtual models during the operation requires for a model update. The NEAR project, Neuroendoscopy towards Augmented Reality, describes a new camera calibration model for high distorted lenses and introduces the concept of active endoscopes endowed with with navigation, camera calibration, augmented reality and triangulation modules

Enhanced Reality Visualization in a Surgical Environment

Enhanced reality visualization is the process of enhancing an image by adding to it information which is not present in the original image. A wide variety of information can be added to an image ranging from hidden lines or surfaces to textual or iconic data about a particular part of the image. Enhanced reality visualization is particularly well suited to neurosurgery. By rendering brain structures which are not visible, at the correct location in an image of a patient's head, the surgeon is essentially provided with X-ray vision. He can visualize the spatial relationship between brain structures before he performs a craniotomy and during the surgery he can see what's under the next layer before he cuts through. Given a video image of the patient and a three dimensional model of the patient's brain the problem enhanced reality visualization faces is to render the model from the correct viewpoint and overlay it on the original image. The relationship between the coordinate frames of the patient, the patient's internal anatomy scans and the image plane of the camera observing the patient must be established. This problem is closely related to the camera calibration problem. This report presents a new approach to finding this relationship and develops a system for performing enhanced reality visualization in a surgical environment. Immediately prior to surgery a few circular fiducials are placed near the surgical site. An initial registration of video and internal data is performed using a laser scanner. Following this, our method is fully automatic, runs in nearly real-time, is accurate to within a pixel, allows both patient and camera motion, automatically corrects for changes to the internal camera parameters (focal length, focus, aperture, etc.) and requires only a single image