External Navigation System Research Articles

An endoscopic chisel: intraoperative imaging carves 3D anatomical models.

Preoperative imaging plays a pivotal role in sinus surgery where CTs offer patient-specific insights of complex anatomy, enabling real-time intraoperative navigation to complement endoscopy imaging. However, surgery elicits anatomical changes not represented in the preoperative model, generating an inaccurate basis for navigation during surgery progression. We propose a first vision-based approach to update the preoperative 3D anatomical model leveraging intraoperative endoscopic video for navigated sinus surgery where relative camera poses are known. We rely on comparisons of intraoperative monocular depth estimates and preoperative depth renders to identify modified regions. The new depths are integrated in these regions through volumetric fusion in a truncated signed distance function representation to generate an intraoperative 3D model that reflects tissue manipulation RESULTS: We quantitatively evaluate our approach by sequentially updating models for a five-step surgical progression in an ex vivo specimen. We compute the error between correspondences from the updated model and ground-truth intraoperative CT in the region of anatomical modification. The resulting models show a decrease in error during surgical progression as opposed to increasing when no update is employed. Our findings suggest that preoperative 3D anatomical models can be updated using intraoperative endoscopy video in navigated sinus surgery. Future work will investigate improvements to monocular depth estimation as well as removing the need for external navigation systems. The resulting ability to continuously update the patient model may provide surgeons with a more precise understanding of the current anatomical state and paves the way toward a digital twin paradigm for sinus surgery.

Determining the invariant of inter-frame processing for constructing the image similarity metric

The relevance of modeling digital images is determined by the need to implement approaches in the study of localization and identification of objects in order to reduce the amount of data. In this paper, the study object is the topology of a discrete two-dimensional image within the framework of the problem of determining the invariants of diffeomorphic transformations. Geographic information objects (GIOs) refer to objects that are on a given surface or objects that locally change the surface. With regard to objects, it is assumed that the change in their geolocation in the process of forming both single images and an extended series of frames obtained in the process of continuous monitoring is insignificant. In the process of scanning the surface, possible changes in the position of the image source are taken into account, for example, such as yawing, rolling, and pitch in the case of unmanned aerial vehicles (UAVs). These maneuvers are represented as a group of diffeomorphisms that are controlled by the internal gyroscopes of the carrier and the external navigation system. Based on the studies reported here, the initial ontology of digital images (ODI) has been determined by using the model of color spaces and functions of a special kind. The presence of an ontology makes it possible to build an adequate topology of color distribution in the image and take into account the specificity of the distribution of different colors in a digital image. The study results indicate that a promising method is to determine the similarity by constructing a color atlas structure graph (CASG) based on ODI and by determining invariants as a fragment of CASG inherited by all images in the sequence. The scope and conditions for the practical use of the result include its application to the analysis of images by methods of artificial intelligence

СРАВНИТЕЛЬНЫЙ АНАЛИЗ ЦЕНТРАЛИЗОВАННОГО И ДЕЦЕНТРАЛИЗОВАННОГО АЛГОРИТМОВ ДВИЖЕНИЯ СТРОЕМ БЛА МУЛЬТИКОПТЕРНОГО ТИПА

The development of robotics makes their group application relevant for solving varioustasks. The effectiveness of performing the tasks of detecting and determining the coordinates ofobjects by a group of robots significantly depends on the accuracy of maintaining a given formation.In this regard, the task of determining motion planning algorithms that ensure the greatestaccuracy of maintaining a given formation is of practical interest. This article is devoted to thestudy of the accuracy of maintaining the formation of a multicopter-type UAV group using a centralizedmotion planning algorithm and a decentralized algorithm. The centralized algorithm usesa master UAV, which transmits its coordinates to the slave UAVs. Based on the coordinates obtainedand the given framework of the formation, the guided UAVs plan their movement. In a decentralizedsystem, neighboring UAV groups transmit their coordinates to each other, on the basisof which the movement of a separate UAV is planned. The accuracy of the control system is investigateddepending on the errors of the navigation system and the frequency of updating data on theposition of the leading or neighboring UAVs. It is assumed that the group's UAVs determine their coordinates in discrete moments of time using an external navigation system. Centralized anddecentralized algorithms are worked out by the same motion control system. The algorithms areinvestigated in this article by numerical modeling methods. In the process of simulation, models ofkinematics, dynamics and actuators are taken into account, as well as models for the formation oferrors in the navigation system. It is shown that the de-centralized algorithm of group motionplanning provides higher accuracy compared to the centralized algorithm. However, the technicalimplementation of a decentralized algorithm is more complicated from the point of view of organizinga group communication system. In a centralized system, data transmission from the masterUAV to the slave should be implemented. In a decentralized system, it is required to implementnetwork communication.

Use of a neural network to generate a whole atrium 3D reconstruction of electrographic flow and basket catheter geometry from biosignals alone

Abstract Funding Acknowledgements Type of funding sources: None. Background Electrographic flow (EGF) mapping detects and quantifies patterns of electrical wavefront propagation in the atrial myocardium from basket catheter recordings. However, no single catheter can map the entire endocardial surface simultaneously. Creating panoramic maps of the whole atrium may be possible by reconstructing multiple basket positions obtained within a few minutes of each other. Purpose Present a method of 3D reconstruction of EGF maps generated from individual basket recordings using QRS morphologies and CT anatomies. Methods EGF maps were generated from unipolar signals recorded over 1 minute from 64-pole basket catheters. QRS morphologies recorded by each individual electrode were used to train a neural network (NN) on the reconstruction of the basket geometries in 3D. The NN uses the similarities between QRS morphologies to represent multiple recordings in one coherent 3D space and spatially integrate phenomena across multiple recordings without any external navigation system. Results A basket catheter was placed in the superior vena cava of a chronic AF canine model. The catheter was manually pulled back in steps of 5mm under fluoroscopic supervision. After reconstruction of the 3D electrode positions, a successive displacement of 3.5±1.2mm per step was reproduced. We applied the proposed method on recordings of 18 patients where an EGF source was identified. Independently, an expert determined the source locations on a 3rd party navigation system, based on 10 predefined regions in the left atrium. In 83% of the cases, the proposed method projected the sources in the same or adjacent region. Conclusion Novel 3D reconstruction from QRS signatures enables integration of EGF maps from multiple basket recordings that can be aligned with CT anatomy. Due to the real-time EGF map acquisition, synthesizing maps from more than 1 basket position provides a more panoramic visualization of complex atrial flow patterns.

An Operational Concept for Correcting Navigation Drift During Sonar Surveys of the Seafloor

The accumulation of navigation errors (drift) is a problem in many applications of autonomous underwater vehicles (AUVs), particularly during long-duration underwater surveys. Traditional methods for correcting drift require either surfacing of the vehicle for a global navigation satellite systemupdate or use of an independent acoustic positioning system. These methods may not be desirable or possible due to mission constraints. We propose a solution to this problem completely underwater and without the aid of external navigation systems. The approach is based on an operational concept that uses a modified paired-track survey pattern combined with through-the-sensor navigation corrections from a seafloor imaging sonar. We describe the operational concept, derive a model for its performance limits, validate this model, and demonstrate the concept with real experiments at sea. Using this approach, we provide an opportunity to use either coherent or incoherent through-the-sensor positioning corrections for a mission length increase of only the product of the intratrack spacing and the number of track pairs. We show results from a proof-of-principle experiment using data collected by the ${\text{300-kHz}}$ synthetic aperture sonar of the NATO Centre for Maritime Research and Experimentation's Minehunting Unmanned underwater vehicle for Shallow water Covert Littoral Expeditions.

A Vehicle System for Autonomous Relative Survey of In-Water Ships

A new vehicle system for relative inspection of in-water ship hulls has been developed, wherein a Doppler velocity logger is used to navigate relative to the surface being inspected, and imaging is performed with a DIDSON sonar. The system is capable of working with no compass or external navigation system, and in zero visibility waters. The ability to locate and lock onto a wall, and then perform full-coverage survey is demonstrated in several field tests.

Recovering the X-ray projection geometry for three-dimensional tomographic reconstruction with additional sensors: Attached camera versus external navigation system

Three-dimensional tomographic reconstruction using intra-operative mobile C-arms could provide physicians with new and exciting tools for image-guided surgery. Recovery of the projection geometry of mobile X-ray systems is a crucial step for such reconstruction procedures. Recent work on medical imaging describes the use of optical or electro-magnetic sensor systems in order to navigate surgical instruments. These systems can also be used for the estimation of C-arm motion, and therefore for the recovery of the projection geometry of the X-ray C-arm. In this case, the mathematical problem that needs to be solved is equivalent to the hand–eye calibration well studied by both the computer vision and robotics community. We first study the recovery of the motion and projection geometry using five different hand–eye calibration methods proposed in the literature. The optical navigation system POLARIS from Northern Digital Inc. was used in our experiments. The results of the estimated motion and projection geometry using the five hand–eye calibration methods are compared with the same results obtained using an off-the-shelf CCD camera attached to the mobile C-arm. The experimental results include three-dimensional tomographic reconstruction results using our mobile C-arm. We show that even though the motion of the C-arm is more precisely recovered using the navigation system, the projection geometry is better estimated using the attached CCD camera.

Application of Error Correcting Codes to Navigation of Autonomous Mobile Robots in a CIM Environment

A new concept for navigation of mobile robots based on the planary coded environment (PLACER) is presented, which enables the coordination of several mobile robots in a real manufacturing environment. It is a path independent external navigation system with passive environment structuring over the entire movement area of the robots. This area is completely covered with tiles, each containing the coordinates of its centre point inscribed using an error correcting code

Satellite Navigation: GPS Inadequacies: Comparative Study into Solutions for Civil Aviation

The Global Positioning System (GPS) will be an extremely high-performance satellite-based navigation system which is expected to provide a sole means air navigation service for most aeronautical flight phases. It will be particularly suitable for ‘en route’, ‘terminal’ and ‘non-precision approach’ phases, thus providing substantial savings on aircraft operating costs.However, GPS has three major disadvantages for civil aviation: (1) Insufficient system integrity, since satellites can transmit erroneous information for two hours before being repaired or neutralized. In such an event, the many simultaneous users of the satellite that has lost its integrity can derive false positions and remain unaware of the problem. (2) Availability constrained by the limited number of satellites. Users are then unable to obtain a position fix or else obtain a result with significantly degraded performance. (3) Deliberate spatio-temporal degradation (selective availability) of system performance, the characteristics of which are not fully known or defined.Many solutions to these problems have been put forward. One concept uses the redundancy of the GPS system itself (receiver autonomous integrity monitoring). Another set of solutions is based on complementary information from autonomous navigation equipment (altimeter, clock, inertial system) or external navigation systems already available or being developed (Omega, Loran-C, GLONASS). A third type of solution is to implement a system by which to monitor the status of the GPS satellites and broadcast the information to users.This paper reports on the different techniques put forward and uses different qualitative criteria (technical feasibility, cost, political independence, etc.) to assess their suitability for civil aviation applications. The comparison leads to the recommendation of a system to monitor the status of the GPS satellites and broadcast the information to users. The characteristics of such messages would be as similar as possible to those of GPS messages.

Use of swath data in realtime navigation by pattern recognition

Abstract A new method is proposed with the aim of reducing dead reckoning error (DRE) during multibeam echosounding survey in deep ocean. Bathymetric data is used in this method to estimate DRE in position fixing. This method can be activated at any desired interval to check the DRE accumulation in addition to available external navigation systems. A pattern recognition algorithm is developed to quantify the shift in position of a selected bathymetric feature that has been observed already once. This difference is used to correct the position fixing and navigation data.