Automated Registration and Real-Time Calibration Methods for a Mixed Reality Neurosurgical Navigation System

Computer-assisted navigation techniques are used to optimise component placement and alignment in total hip replacement. It has developed in the last 10years but despite its advantages only 0.3% of all total hip replacements in England and Wales are done using computer navigation. One of the reasons for this is that computer-assisted technology increases operative time. A new method of pelvic registration has been developed without the need to register the anterior pelvic plane (BrainLab hip 6.0) which has shown to improve the accuracy of THR. The purpose of this study was to find out if the new method reduces the operating time. This was a retrospective analysis of comparing operating time in computer navigated primary uncemented total hip replacement using two methods of registration. Group 1 included 128 cases that were performed using BrainLab versions 2.1-5.1. This version relied on the acquisition of the anterior pelvic plane for registration. Group 2 included 128 cases that were performed using the newest navigation software, BrainLab hip 6.0 (registration possible with the patient in the lateral decubitus position). The operating time was 65.79 (40-98) minutes using the old method of registration and was 50.87 (33-74) minutes using the new method of registration. This difference was statistically significant. The body mass index (BMI) was comparable in both groups. The study supports the use of new method of registration in improving the operating time in computer navigated primary uncemented total hip replacements.

Binocular vision systems play an important role in computer vision, and high-precision system calibration is a necessary and indispensable process. In this paper, an improved calibration method for binocular stereo vision measurement systems based on arbitrary translations and 3D-connection information is proposed. First, a new method for calibrating the intrinsic parameters of binocular vision system based on two translations with an arbitrary angle difference is presented, which reduces the effect of the deviation of the motion actuator on calibration accuracy. This method is simpler and more accurate than existing active-vision calibration methods and can provide a better initial value for the determination of extrinsic parameters. Second, a 3D-connection calibration and optimization method is developed that links the information of the calibration target in different positions, further improving the accuracy of the system calibration. Calibration experiments show that the calibration error can be reduced to 0.09%, outperforming traditional methods for the experiments of this study.

The mirror in the high-energy laser beam combining system needs to make a fast and high-precision pointing adjustment before working. A two-dimensional electrically controlled adjusting mirror was designed. The main body of the system adopted an integrated flexible support design, the drive adopted a stepping motor and a deceleration mechanism to drive the screw, the precision measurement of the mirror deflection angle adopted an eddy current sensor, and the digital signal processor (DSP) was adopted as the main control module. The working principle and design of the system were analyzed, and the system calibration method as well as the control algorithm were deeply studied. In order to meet the requirements of system adjustment speed, the S-shaped acceleration and deceleration algorithm was adopted as the control algorithm of adjusting mirror, and the system calibration method with piecewise linearity was adopted. Finally, the system was tested experimentally. The experimental results show that within the angle range of ±500″, the in-position time of adjusting mirror is within 3 s, and the control error is less than 2″, which can meet the system requirements.

The precision and stability of the Robot-Assisted Percutaneous Puncture (RAPP) system have become increasingly crucial with the widespread integration of robotic technology in the field of medicine. The accurate calibration of the RAPP system prior to surgery significantly influences target positioning performance. This study proposes a novel system calibration method that simultaneously addresses system hand–eye calibration and robot kinematic parameters calibration, thereby enhancing the surgery success rate and ensuring patient safety. Initially, a Closed-loop Hand–eye Calibration (CHC) method is employed to rapidly establish transformation relationships among system components. These CHC results are then integrated with nominal robot kinematic parameters to preliminarily determine the system calibration parameters. Subsequently, a hybrid algorithm, combining the regularized Levenberg–Marquardt (LM) algorithm and a particle filtering algorithm, is utilized to accurately estimate the system calibration parameters in stages. Numerical simulations and puncture experiments were conducted using the proposed system calibration method and other comparative methods. The experimental results revealed that, among several comparative methods, the approach presented in this paper yields the greatest improvement in the puncture accuracy of the RAPP system, demonstrating the accuracy and effectiveness of this method. In conclusion, this calibration method significantly contributes to enhancing the precision, operational capability, and safety of the RAPP system in practical applications.

Mixed reality (MR) surgical navigation systems have achieved notable success in procedures involving rigid anatomical structures but face substantial challenges in soft tissue interventions due to intraoperative deformation. Current literature reveals a significant gap in MR-based navigation systems that provide quantitative validation through subsurface targeting experiments representative of clinical workflow. This study presents a comprehensive MR surgical navigation platform for liver interventions enhanced with new features including soft-tissue deformation correction, real-time microwave (MW) probe trajectory visualization, and distance-to-target measurement capabilities. In addition to novel platform design, the first standardized experimental protocol specifically designed for validating subsurface targeting accuracy in the context of MR surgical navigation systems has been established. The validation methodology provides a quantitative targeting evaluation that can be universally adopted for comparative analysis with other MR approaches. Using the MW probe navigation capabilities, surgical workflow maintained clinically viable efficiency with a navigation-to-target time of 5.5 ± 1.3 minutes per targeting session that spanned 13 subsurface targets per session. With respect to the correction for soft-tissue deformations, our non-rigid registration method (NRM) demonstrated superior performance compared to rigid registration method (RRM), achieving 41.3% reduction in user-navigated targeting error (from 10.4 ± 3.9 mm to 6.1 ± 2.8 mm) and 42.3% reduction in ground-truth measured targeting error (from 13.0 ± 5.5 mm to 7.5 ± 3.3 mm). Other novelties to the platform design are an integrated real-time ablation zone prediction and visualization tool as a potential direction for clinical application. The advancement positions the technology as a powerful surgical guidance approach for hepatic interventions. This research is the first to establish a validation framework standard for MR surgical navigation system which successfully compensates for soft tissue deformation.

To present a generic geometric calibration method for tomographic imaging systems with flat-panel detectors in a very detailed manner, in the aim to provide a useful tool to the public domain. The method is based on a projection matrix which represents a mapping from 3D object coordinate system to 2D projection image plane. The projection matrix can be determined experimentally through the imaging of a phantom of known marker geometry. Accurate implementation was accomplished through direct computation algorithms, including a novel ellipse fitting using singular value decomposition and data normalization. Benefits of the method include: (1) It is capable of being applied to systems of different scan trajectories, source-detector alignments, and detector orientations; (2) projection matrices can be utilized in image reconstructions or in the extraction of explicit geometrical parameters; and (3) the method imposes minimal limits on the design of calibration phantom. C++ programs that calculate projection matrices and extract geometric parameters from them are also provided. For validation, the calibration method was applied to the computer simulation of a cone-beam CT system, as well as to three tomosynthesis prototypes of different source-detector movement patterns: Source and detector rotating synchronizedly; source rotating and detector wobbling; and source rotating and detector staying stationary. Projection matrices were computed on a view by view basis. Geometric parameters extracted from projection matrices were consistent with actual settings. Images were reconstructed by directly using projection matrices, and were compared to virtual Shepp-Logan image for CT simulation and to central projection images of CIRS breast phantoms for tomosynthesis prototypes. They showed no obvious distortion or blurring, indicating the high quality of geometric calibration results. When the computed central ray offsets were perturbed with Gaussian noises of 1 pixel standard deviation, the reconstructed image showed apparent distortion, which further demonstrated the accuracy of the geometric calibration method. The method is suitable for tomographic imaging systems with flat-panel detectors.

Registration of the patient body and virtual 3D plan is an initial but very fundamental procedure for accurately using the navigation system. Currently, there are two commonly used registration methods, i.e., point registration and intraoperative CT registration, which are suitable for different kinds of operative scenarios. By now, there is no literature reporting about how to choose between these two registration methods during using the navigation systems. In this study, we respectively performed 12 simulated osteotomies based on the point registration method and intraoperative registration method during using the navigation system. Two statistical tests were done based on the surgical errors of osteotomy surgeries using these two registration methods. Specifically, T-test result (p<0.001) indicated the intraoperative CT registration performed better than point registration. Besides, equivalence test of the two registration methods (Rg=1.00 mm) suggested that the two registration methods perform equivalently while using the navigation system. Moreover, we have shared the surgeons some practical suggestions about how to choose between these two registration methods during using the navigation system.

Purpose: System calibration of a micro CT scanner for anatomic imaging of small animals. Method and Materials: A phantom was constructed with lead ball bearings (200 μm in diameter) and scanned with a micro CT scanner designed and built in our laboratory. A general mathematical algorithm was developed to locate the X‐ray focal spot and measure the source to detector distance (SID) and the azimuthal rotation of the detector with information acquired from the projection image of the phantom. A wire phantom (0.070mm Ni‐Cd) was scanned to calibrate the angle measurement of the stepping motor which drives the rotating stage of the scanner, and also to measure the source to iso‐center distance (SIC). An array of different objects was scanned and reconstructed with these calibrated parameters to evaluate the calibration result. Results: With the calibration procedure described, critical system parameters required for cone beam reconstruction including SIC, SID, x‐ray focal spot location, detector rotation angle, and stage rotation angle were measured with high precision. Subsequent phantom testing demonstrated the accuracy of this calibration method by qualitative artifact assessment, and spatial resolution metrics (MTF) also demonstrated excellent performance. Conclusion: A simple but precise method for system calibration of a cone beam micro CT system using flat panel detector was developed. This method is likely useful for CT systems across different scales (from micro CT to human CT).

A novel dynamic electromagnetic tracking navigation system for distal locking of intramedullary nails

Hypertensive intracerebral hemorrhage (HICH) is an intracerebral bleeding disease that affects 2.5 per 10,000 people worldwide each year. An effective way to cure this disease is puncture through the dura with a brain puncture drill and tube; the accuracy of the insertion determines the quality of the surgery. In recent decades, surgical navigation systems have been widely used to improve the accuracy of surgery and minimize risks. Augmented reality- and mixed reality-based surgical navigation is a promising new technology for surgical navigation in the clinic, aiming to improve the safety and accuracy of the operation. In this study, we present a novel multimodel mixed reality navigation system for HICH surgery in which medical images and virtual anatomical structures can be aligned intraoperatively with the actual structures of the patient in a head-mounted device and adjusted when the patient moves in real time while under local anesthesia; this approach can help the surgeon intuitively perform intraoperative navigation. A novel registration method is used to register the holographic space and serves as an intraoperative optical tracker, and a method for calibrating the HICH surgical tools is used to track the tools in real time. The results of phantom experiments revealed a mean registration error of 1.03mm and an average time consumption of 12.9min. In clinical usage, the registration error was 1.94mm, and the time consumption was 14.2min, showing that this system is sufficiently accurate and effective for clinical application.

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A new adaptive method that automatically removes mesh elements in the area of the resected tumor, thereby handling deformation in the presence of resection is presented. To improve the user experience, we also present a new way of using mixed reality with ultrasound, MRI, and CT.Materials and methods: This study focuses on 30 glioma surgeries performed at two different hospitals, many of which involved the resection of significant tumor volumes. An Adaptive Physics-Based Non-Rigid Registration method (A-PBNRR) registers preoperative and intraoperative MRI for each patient. The results are compared with three other readily available registration methods: a rigid registration implemented in 3D Slicer v4.4.0; a B-Spline non-rigid registration implemented in 3D Slicer v4.4.0; and PBNRR implemented in ITKv4.7.0, upon which A-PBNRR was based. Three measures were employed to facilitate a comprehensive evaluation of the registration accuracy: (i) visual assessment, (ii) a Hausdorff Distance-based metric, and (iii) a landmark-based approach using anatomical points identified by a neurosurgeon.Results: The A-PBNRR using multi-tissue mesh adaptation improved the accuracy of deformable registration by more than five times compared to rigid and traditional physics based non-rigid registration, and four times compared to B-Spline interpolation methods which are part of ITK and 3D Slicer. Performance analysis showed that A-PBNRR could be applied, on average, in <2 min, achieving desirable speed for use in a clinical setting.Conclusions: The A-PBNRR method performed significantly better than other readily available registration methods at modeling deformation in the presence of resection. Both the registration accuracy and performance proved sufficient to be of clinical value in the operating room. A-PBNRR, coupled with the mixed reality system, presents a powerful and affordable solution compared to current neuronavigation systems.

: The Copperhead stockpile surveillance program presently being developed by the Advanced Technologies Laboratory, ARDEC, is a highly automated software driven test system. It is designed to test the Copperhead round's seeker, electronics package, guidance, and control systems. The data obtained will be used to identify trends in round performance and subsequently provide a means of predicting future round reliability. This report describes the software and related hardware used to acquire test data for the Copperhead stockpile surveillance program. It outlines their interaction and provides an example of how the test system is used. Methods for system calibration are also presented as well as a scheme for sampling data in bursts. Selected portions of in-house developed software are also discussed.

Absolute accuracy of the line-focus-beam (LFB) acoustic microscopy system is investigated for measurements of the leaky surface acoustic wave (LSAW) velocity and attenuation, and a method of system calibration is proposed. In order to discuss the accuracy, it is necessary to introduce a standard specimen whose bulk acoustic properties, (e.g., the independent elastic constants and density) are measured with high accuracy. Single crystal substrates of gadolinium gallium garnet (GGG) are taken as standard specimens. The LSAW propagation characteristics are measured and compared with the calculated results using the measured bulk acoustic properties. Calibration is demonstrated for the system using two LFB acoustic lens devices with a cylindrical concave surface of 1-mm radius in the frequency range 100 to 300 MHz.

This paper explores the theory and algorithm for the measurement and reconstruction of line industrial objects based on CAD representation, and proposes a mathematical model for line photogrammetry. In the model, the geometric elements based on CAD representation describing industrial objects are considered as unknowns and match directly from image to object. Furthermore, this paper presents an application prototype which includes the system configuration and the method of system calibration. Finally, the measurement results and a discussion are put afterwards.

To determine the shape of a complex object with vertical measurement mode and higher accuracy, a novel modulation measuring profilometry realizing auto-synchronous phase shifting and vertical scanning is proposed. Coaxial optical system for projection and observation instead of triangulation system is adopted to avoid shadow and occlusion. In the projecting system, sinusoidal grating is perpendicular to optical axis. For moving the grating along a direction at a certain angle to optical axis, 1D precision translation platform is applied to achieve purposes of both phase-shifting and vertical scanning. A series of fringe patterns with different modulation variations are captured by a CCD camera while scanning. The profile of the tested object can be reconstructed by the relationship between the height values and the modulation distributions. Unlike the previous method based on Fourier transform for 2D fringe pattern, the modulation maps are calculated from the intensity curve formed by the points with definite pixel coordinates in the captured fringe patterns. The paper gives the principle of the proposed method, the set-up of measurement system and the method for system calibration. Computer simulation and experiment results proved its feasibility.