Static Reconstruction Research Articles

A Cosmetic Surgical Approach Effectively Reconstructed Facial Nerve Paralysis.

Summary:In general, facial nerve palsy is treated by reconstructive surgeons, and the role of cosmetic surgeons is largely seen as secondary. The present report describes a case of refractory facial nerve palsy that arose after malignant parotid-tumor resection and high-dose radiotherapy, and that we reconstructed with a combination of cosmetic and reconstructive procedures. The procedures consisted of facelift techniques (lateral SMASectomy, creation of a nasolabial fold with three suture loops anchored at the temporal fascia, and frontal lift), a new wrinkle-removing technique wherein the frontal-muscle function was disrupted, and excision of surplus skin to rejuvenate the face. The outcomes were good, including at 1 year after surgery, and the 71-year-old patient expressed considerable satisfaction. The frontalis muscle resection effectively removed the wrinkles, helped balance the left and right sides, and permitted anti-aging surgery. This procedure has permanent effects, unlike other methods (eg, botulinum-toxin injections) that serve to weaken facial muscle function. It is notable that despite the high-dose radiotherapy the patient had received and the resulting extensive subcutaneous-tissue adhesion, our surgical protocol was relatively easy to perform as well as highly effective. Thus, even static reconstruction can give great hope and satisfaction to patients with facial nerve palsy.

HUMANNET-A Two-Tiered Deep Neural Network Architecture for Self-Occluding Humanoid Pose Reconstruction.

Majority of current research focuses on a single static object reconstruction from a given pointcloud. However, the existing approaches are not applicable to real world applications such as dynamic and morphing scene reconstruction. To solve this, we propose a novel two-tiered deep neural network architecture, which is capable of reconstructing self-obstructed human-like morphing shapes from a depth frame in conjunction with cameras intrinsic parameters. The tests were performed using on custom dataset generated using a combination of AMASS and MoVi datasets. The proposed network achieved Jaccards’ Index of 0.7907 for the first tier, which is used to extract region of interest from the point cloud. The second tier of the network has achieved Earth Mover’s distance of 0.0256 and Chamfer distance of 0.276, indicating good experimental results. Further, subjective reconstruction results inspection shows strong predictive capabilities of the network, with the solution being able to reconstruct limb positions from very few object details.

Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging

Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of UAVs in a dynamic environment, including their static and dynamic perception ability. Specifically, both three-dimensional reconstruction for a static scene and localization for moving objects are required. Simultaneous Localization And Mapping technology has made great progress in static scene structure reconstruction and UAV self-motion estimation. However, accurate real-time localization of moving objects is still challenging. In this article, a global averaging based localization method is proposed to locate moving objects for a small UAV platform. Inspired by global structure from motion, this idea is applied to the localization of moving objects. To solve moving object localization, the relative motion estimation and global position optimisation methods are proposed. The proposed method was tested in various scenarios with a several trajectories. The extensive experimental results demonstrate the robustness and effectiveness of the proposed method.

Auto-Refining Reconstruction Algorithm for Recreation of Limited Angle Humanoid Depth Data.

With the majority of research, in relation to 3D object reconstruction, focusing on single static synthetic object reconstruction, there is a need for a method capable of reconstructing morphing objects in dynamic scenes without external influence. However, such research requires a time-consuming creation of real world object ground truths. To solve this, we propose a novel three-staged deep adversarial neural network architecture capable of denoising and refining real-world depth sensor input for full human body posture reconstruction. The proposed network has achieved Earth Mover and Chamfer distances of and on synthetic datasets, respectively, which indicates on-par experimental results with other approaches, in addition to the ability of reconstructing from maskless real world depth frames. Additional visual inspection to the reconstructed pointclouds has shown that the suggested approach manages to deal with the majority of the real world depth sensor noise, with the exception of large deformities to the depth field.

Dynamic to Static Lidar Scan Reconstruction Using Adversarially Trained Auto Encoder

Accurate reconstruction of static environments from LiDAR scans of scenes containing dynamic objects, which we refer to as Dynamic to Static Translation (DST), is an important area of research in Autonomous Navigation. This problem has been recently explored for visual SLAM, but to the best of our knowledge no work has been attempted to address DST for LiDAR scans. The problem is of critical importance due to wide-spread adoption of LiDAR in Autonomous Vehicles. We show that state-of the art methods developed for the visual domain when adapted for LiDAR scans perform poorly. We develop DSLR, a deep generative model which learns a mapping between dynamic scan to its static counterpart through an adversarially trained autoencoder. Our model yields the first solution for DST on LiDAR that generates static scans without using explicit segmentation labels. DSLR cannot always be applied to real world data due to lack of paired dynamic-static scans. Using Unsupervised Domain Adaptation, we propose DSLR-UDA for transfer to real world data and experimentally show that this performs well in real world settings. Additionally, if segmentation information is available, we extend DSLR to DSLR-Seg to further improve the reconstruction quality. DSLR gives the state of the art performance on simulated and real-world datasets and also shows at least 4× improvement. We show that DSLR, unlike the existing baselines, is a practically viable model with its reconstruction quality within the tolerable limits for tasks pertaining to autonomous navigation like SLAM in dynamic environments.

Encode–decode network with fully connected CRF for dynamic objects detection and static maps reconstruction

The key of robots operating autonomously in dynamic environments is understanding the dynamic characteristics of objects. This paper aims to detect dynamic objects and reconstruct 3D static maps from consecutive scans of scenes. Our work starts from an encode–decode network, which receives two range maps provided by a Velodyne HDL-64 laser scanner and outputs dynamic probability of each point. Since the soft segmentation produced by the network tends to be smooth, a 3D fully connected CRF (Conditional Random Field) is proposed to improve the segmentation performance. Experiments on both the public datasets and real-word platform demonstrate the effectiveness of our method.

Tips and Pearls for Recovering Symmetry After Facial Palsy Using a Tendon Sling: Our 20-Year Experience

Background: In facial palsy reconstruction, static techniques with the use of slings can improve the appearance and functionality of the paralyzed face and may be used in patients who cannot undergo complex surgeries or as an ancillary procedure to a dynamic reconstruction. The objective of this study was to assess the improvement in facial symmetry and quality of life among older patients with flaccid facial palsy with the use of a plantaris tendon sling. Methods: A total of 46 patients who had undergone a static reconstruction with the plantaris tendon sling were studied. The surgical technique is detailed emphasizing the tips and pearls. Results: The displacement of the oral commissure was assessed with the FACIAL CLIMA demonstrating a mean elevation of 1.5 ± 0.4 cm and an improvement of 97 ± 7% in the recovery of oral commissure symmetry 2 years after the surgery, whereas the Sunnybrook Facial Grading System showed an improvement of symmetry at rest (-15 ± 5) at 2 years. The Facial Disability Score indicated an improvement of the physical disability (+73.5 ± 14) as well as the social impairment (+21 ± 7) at 1 year postoperatively. Patients were followed for a median of 2 years (range 2-6 years). Conclusions: The use of tendon slings for static facial paralysis reconstruction is a reliable technique with no functional sequelae and good long-term results.

Evaluation of Golden-Angle-Sampled Dynamic Contrast-Enhanced MRI Reconstruction Using Objective Image Quality Measures: A Simulated Phantom Study.

We aim to extend the use of image quality metrics (IQMs) from static magnetic resonance imaging (MRI) applications to dynamic MRI studies. We assessed the use of 2 IQMs, the root mean square error and structural similarity index, in evaluating the reconstruction of quantitative dynamic contrast-enhanced (DCE) MRI data acquired using golden-angle sampling and compressed sensing (CS). To address the difficulty of obtaining ground-truth knowledge of parameters describing dynamics in real patient data, we developed a Matlab simulation framework to assess quantitative CS-DCE-MRI. We began by validating the response of each IQM to the CS-MRI reconstruction process using static data and the performance of our simulation framework with simple dynamic data. We then extended the simulations to the more realistic extended Tofts model. When assessing the Tofts model, we tested 4 different methods of selecting a reference image for the IQMs. Results from the retrospective static CS-MRI reconstructions showed that each IQM is responsive to the CS-MRI reconstruction process. Simulations of a simple contrast evolution model validated the performance of our framework. Despite the complexity of the Tofts model, both IQM scores correlated well with the recovery accuracy of a central model parameter for all reference cases studied. This finding may form the basis of algorithms for automated selection of image reconstruction aspects, such as temporal resolution, in golden-angle-sampled CS-DCE-MRI. These further suggest that objective measures of image quality may find use in general dynamic MRI applications.

Nonstationary Image Reconstruction in Ultrasonic Transmission Tomography Using Kalman Filter and Dimension Reduction

As a noninvasive and nonradiation imaging modality, ultrasonic transmission tomography (UTT) has gained much attention in process parameter detections, such as multiphase flow measurement and combustion diagnosis. However, traditional static UTT image reconstruction methods suffer from the problems of image smearing and blurring when reconstructing time-varying process parameters. To overcome this problem, a nonstationary UTT image reconstruction method is proposed based on the Bayesian inversion framework, where the nonstationary UTT inverse problem is formulated as a state estimation problem using a pair of state evolution and observation update equations. The nonstationary UTT inverse problem is solved by the Kalman filter, and a prior-based dimension reduction method is proposed to reduce the computational complexity. In addition, a dimension reduction Kalman smoother is proposed and applied for postprocessing the Kalman filter results, which can improve the imaging quality, especially for the initial states. A series of numerical and experimental tests are carried out to evaluate the performance of the proposed methods. The results show that the proposed nonstationary UTT image reconstruction methods have higher temporal resolution and better imaging quality in nonstationary process parameter estimation compared with the traditional static UTT image reconstruction methods.

Nonrigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS.

PurposeWith the recent introduction of the MR‐LINAC, an MR‐scanner combined with a radiotherapy LINAC, MR‐based motion estimation has become of increasing interest to (retrospectively) characterize tumor and organs‐at‐risk motion during radiotherapy. To this extent, we introduce low‐rank MR‐MOTUS, a framework to retrospectively reconstruct time‐resolved nonrigid 3D+t motion fields from a single low‐resolution reference image and prospectively undersampled k‐space data acquired during motion.TheoryLow‐rank MR‐MOTUS exploits spatiotemporal correlations in internal body motion with a low‐rank motion model, and inverts a signal model that relates motion fields directly to a reference image and k‐space data. The low‐rank model reduces the degrees‐of‐freedom, memory consumption, and reconstruction times by assuming a factorization of space‐time motion fields in spatial and temporal components.MethodsLow‐rank MR‐MOTUS was employed to estimate motion in 2D/3D abdominothoracic scans and 3D head scans. Data were acquired using golden‐ratio radial readouts. Reconstructed 2D and 3D respiratory motion fields were, respectively, validated against time‐resolved and respiratory‐resolved image reconstructions, and the head motion against static image reconstructions from fully sampled data acquired right before and right after the motion.ResultsResults show that 2D+t respiratory motion can be estimated retrospectively at 40.8 motion fields per second, 3D+t respiratory motion at 7.6 motion fields per second and 3D+t head‐neck motion at 9.3 motion fields per second. The validations show good consistency with image reconstructions.ConclusionsThe proposed framework can estimate time‐resolved nonrigid 3D motion fields, which allows to characterize drifts and intra and inter‐cycle patterns in breathing motion during radiotherapy, and could form the basis for real‐time MR‐guided radiotherapy.

Consensus Recommendations on the Use of 18F-FDG PET/CT in Lung Disease.

PET with 18F-FDG has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and to monitor disease progression and treatment outcomes in lung diseases that interfere with gas exchange through alterations of the pulmonary parenchyma, airways, or vasculature. To date, however, there are no widely accepted standard acquisition protocols or imaging data analysis methods for pulmonary 18F-FDG PET/CT in these diseases, resulting in disparate approaches. Hence, comparison of data across the literature is challenging. To help harmonize the acquisition and analysis and promote reproducibility, we collated details of acquisition protocols and analysis methods from 7 PET centers. From this information and our discussions, we reached the consensus recommendations given here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting.

New Sensing Strategies for Estimation of Global, Exospheric Density

AbstractReliable quantification of the global and time‐dependent structure of the Earth's outermost atmosphere, a vast region known as the exosphere, has long been elusive, owing mainly to the sparse spatial and temporal sampling afforded by exospheric sensing platforms deployed to date. In this paper, we introduce new observing schemes that overcome these historical limitations and enable high‐fidelity, high‐cadence reconstruction of the exospheric density distribution on a global scale. Our approach leverages several state‐of‐the‐art remote sensing capabilities, including (1) wide‐field photometric imaging of exospheric emission, which is created through resonant photon scattering by the exosphere's constituent hydrogen atoms; (2) constellation sensor deployment near lunar orbit, which provides common‐volume sensing; and (3) tomographic inversion of a discretized exospheric emission model that explicitly accounts for the Poisson‐distributed shot noise inherent in the photometric data constraints. Using ensembles of synthetic emission data acquired at various realistic temporal cadences, we evaluate the fidelity of both static density reconstructions, in which the solution is formulated in the context of maximum a posteriori (MAP) estimation, as well as dynamic density reconstructions, which incorporate temporal evolution via Kalman filtering. The numerical results demonstrate that the new sensing strategies are capable of retrieving reliable estimates of exospheric density distribution at unprecedented spatial scales and temporal cadence, in support of numerous high‐priority investigations of Earth's near‐space environment.

MOVING OBJECTS AWARE SENSOR MESH FUSION FOR INDOOR RECONSTRUCTION FROM A COUPLE OF 2D LIDAR SCANS

Abstract. Indoor mapping attracts more attention with the development of 2D and 3D camera and Lidar sensor. Lidar systems can provide a very high resolution and accurate point cloud. When aiming to reconstruct the static part of the scene, moving objects should be detected and removed which can prove challenging. This paper proposes a generic method to merge meshes produced from Lidar data that allows to tackle the issues of moving objects removal and static scene reconstruction at once. The method is adapted to a platform collecting point cloud from two Lidar sensors with different scan direction, which will result in different quality. Firstly, a mesh is efficiently produced from each sensor by exploiting its natural topology. Secondly, a visibility analysis is performed to handle occlusions (due to varying viewpoints) and remove moving objects. Then, a boolean optimization allows to select which triangles should be removed from each mesh. Finally, a stitching method is used to connect the selected mesh pieces. Our method is demonstrated on a Navvis M3 (2D laser ranger system) dataset and compared with Poisson and Delaunay based reconstruction methods.

Static Explosion Field Reconstruction Based on the Improved Biharmonic Spline Interpolation

To obtain the peak pressure distribution of explosion field near the ground, an improved reconstruction method for interpolation of blast overpressure data from the finite measuring points was studied. According to the peak attenuation law of shock wave on the propagation path and the attenuation characteristic of the wave front after passing through the measured points, the polynomial fitting function of peak attenuation of shock wave near the ground is constructed by using the least square method. Using the peak attenuation polynomial of shock wave constrain the radial interpolation of biharmonic spline surface interpolation algorithm (BSSIA) to realize the interpolation conforming the propagation law of shock wave and ensure the interpolation convergence. The root-mean-squared error (RMSE) and the maximum relative error (MRE) before and after the improvement were computed by comparing the peaks with empirical formula data. The improvement is evident as the RMSE decreased from 14.12kPa to 0.22kPa and the MRE decreased from 23.91% to 0.37%. The peak reconstructed by the improved biharmonic spline surface interpolation algorithm (IBSSIA) and BSSIA with test data, the overpressure peak distribution obtained by IBSSIA is in good agreement with empirical result and consistent with the explosion image.

Clinical Evaluation of a Data-Driven Respiratory Gating Algorithm for Whole-Body PET with Continuous Bed Motion

Respiratory gating is the standard to prevent respiration effects from degrading image quality in PET. Data-driven gating (DDG) using signals derived from PET raw data is a promising alternative to gating approaches requiring additional hardware (e.g., pressure-sensitive belt gating [BG]). However, continuous-bed-motion (CBM) scans require dedicated DDG approaches for axially extended PET, compared with DDG for conventional step-and-shoot scans. In this study, a CBM-capable DDG algorithm was investigated in a clinical cohort and compared with BG using optimally gated (OG) and fully motion-corrected (elastic motion correction [EMOCO]) reconstructions. Methods: Fifty-six patients with suspected malignancies in the thorax or abdomen underwent whole-body 18F-FDG CBM PET/CT using DDG and BG. Correlation analyses were performed on both gating signals. Besides static reconstructions, OG and EMOCO reconstructions were used for BG and DDG. The metabolic volume, SUVmax, and SUVmean of lesions were compared among the reconstructions. Additionally, the quality of lesion delineation in the different PET reconstructions was independently evaluated by 3 experts. Results: The global correlation coefficient between BG and DDG signals was 0.48 ± 0.11, peaking at 0.89 ± 0.07 when scanning the kidney and liver region. In total, 196 lesions were analyzed. SUV measurements were significantly higher in BG-OG, DDG-OG, BG-EMOCO, and DDG-EMOCO than in static images (P < 0.001; median SUVmax: static, 14.3 ± 13.4; BG-EMOCO, 19.8 ± 15.7; DDG-EMOCO, 20.5 ± 15.6; BG-OG, 19.6 ± 17.1; and DDG-OG, 18.9 ± 16.6). No significant differences between BG-OG and DDG-OG or between BG-EMOCO and DDG-EMOCO were found. Visual lesion delineation was significantly better in BG-EMOCO and DDG-EMOCO than in static reconstructions (P < 0.001); no significant difference was found when comparing BG and DDG for either EMOCO or OG reconstruction. Conclusion: DDG-based motion compensation of CBM PET acquisitions outperforms static reconstructions, delivering qualities comparable to BG approaches. The new algorithm may be a valuable alternative for CBM PET systems.

The Outcome of the Reconstruction Surgery to Manage the Chronic Collateral Ligament Injury of the Thumb Metacarpophalangeal Joint

Background: Management of chronic collateral ligament injury of the Metacarpophalangeal (MCP) joint, either its Ulnar Collateral Ligament (UCL) or Radial Collateral Ligament (RCL), is challenging. Objectives: In this study, we report the outcome of ligament reconstruction procedure in the treatment of such injuries. Methods: In a retrospective study, the outcomes of static reconstruction surgery of the symptomatic chronic collateral ligament injury of the thumb MCP joint (five RCL and three UCL) were evaluated. We used palmaris longus tendon in four surgeries and flexor carpi radialis tendon in the remaining. The outcome measures included the thumb range of motion, the disabilities of the arm, shoulder, and hand (QuickDASH) questionnaire, pinch and grip strength, visual analog scale, and Kapandji opposition score. Results: Eight patients (6 males and 2 females) with the mean±SD age of 32±7.1 years were included in this study. The Mean±SD duration from the injury to surgery was 66.7±99.5 weeks. The Mean±SD follow-up of the patients was 4.88±1.35 years. The mean pinch and grip strength of the involved hand averaged 98.9% and 100% of the other hand, respectively. Postoperative pain was only noticed in two patients. The Mean±SD postoperative Kapandji opposition score was 9.4±0.7 (range: 8-10). The Mean±SD QuickDASH score was 12.9±1.9 (range: 11-17). The thumb range of motion was similar to the contralateral hand in all but one patient. All the operated joints were stable. A case of mild degenerative joint disease was the only observed postoperative complication. Conclusion: Static reconstruction of chronic collateral ligament injury of the thumb MCP joint provides acceptable results, regardless of the time interval between the injury and surgery.

Real-Time Dynamic 3D Shape Reconstruction with SWIR InGaAs Camera.

In this paper, a real-time, dynamic three-dimensional (3D) shape reconstruction scheme based on the Fourier-transform profilometry (FTP) method is achieved with a short-wave infrared (SWIR) indium gallium arsenide (InGaAs) camera for monitoring applications in low illumination environments. A SWIR 3D shape reconstruction system is built for generating and acquiring the SWIR two-dimensional (2D) fringe pattern of the target. The depth information of the target is reconstructed by employing an improved FTP method, which has the advantages of high reconstruction accuracy and speed. The maximum error in depth for static 3D shape reconstruction is 1.15 mm for a plastic model with a maximum depth of 36 mm. Meanwhile, a real-time 3D shape reconstruction with a frame rate of 25 Hz can be realized by this system, which has great application prospects in real-time dynamic 3D shape reconstruction, such as low illumination monitoring. In addition, for real-time dynamic 3D shape reconstruction, without considering the edge areas, the maximum error in depth among all frames is 1.42 mm for a hemisphere with a depth of 35 mm, and the maximum error of the average of all frames in depth is 0.52 mm.

Evaluation of Patellar Contact Pressure Changes after Static versus Dynamic Medial Patellofemoral Ligament Reconstructions Using a Finite Element Model

Objectives: To evaluate the effect of various medial patellofemoral ligament (MPFL) fixation techniques on patellar pressure compared with the native knee. Methods: A finite element model of the patellofemoral joint consisting of approximately 30,700 nodes and 22,200 elements was created from computed tomography scans of 24 knees with chronic lateral patellar instability. Patellar contact pressures and maximum MPFL graft stress at five positions of flexion (0°, 30°, 60°, 90°, and 120°) were analyzed in three types of MPFL reconstruction (MPFLr): (1) static/anatomic, (2) dynamic, using the adductor magnus tendon (AMT) as the femoral fixation, and (3) dynamic, using the quadriceps tendon as the attachment (medial quadriceps tendon-femoral ligament (MQTFL) reconstruction). Results: In the static/anatomic technique, the patellar contact pressures at 0° and 30° were greater than in the native knee. As in a native knee, the contact pressures at 60°, 90°, and 120° were very low. The maximum MPFL graft stress at 0° and 30° was greater than in a native knee. However, the MPFL graft was loose at 60°, 90°, and 120°, meaning it had no tension. In the dynamic MPFLr using the AMT as a pulley, the patellar contact pressures were like those of a native knee throughout the entire range of motion. However, the maximum stress of the MPFL graft at 0° was less than that of a native ligament. Yet, the maximum MPFL graft stress was greater at 30° than in a native ligament. After 30° of flexion, the MPFL graft loosened, similarly to a native knee. In the dynamic MQTFL reconstruction, the maximum patellar contact pressure was slightly greater than in a normal knee. The maximum stress of the MPFL graft was much greater at 0° and 30° than that of a native MPFL. After 30° of flexion, the MQPFL graft loosened just as in the native knee. Conclusions: The patellar contact pressures after the dynamic MPFLr were like those of the native knee, whereas a static reconstruction resulted in greater pressures, potentially increasing the risk of patellofemoral osteoarthritis in the long term. Therefore, the dynamic MPFLr might be a safer option than a static reconstruction from a biomechanical perspective.

49 Evaluation and optimisation of parametric reconstruction algorithms in FDG PET imaging

Introduction. Recently there has been an increased interest in whole-body dynamic PET protocols for parametric imaging, for better diagnosis and prognosis in oncology. The aim of this study is to evaluate and optimise dynamic (4D) reconstruction algorithms as opposed to standard static (3D) reconstruction algorithms for improved quantification and image quality of glucose metabolic rate parametric images for FDG PET data.

Simple and Robust Intravital Microscopy Procedures in Hybrid TIE2GFP-BALB/c Transgenic Mice.

The endeavor of deciphering intricate phenomena within the field of molecular medicine dictates the necessity to investigate tumor/disease microenvironment real-time on cellular level. We, hereby, design simple and robust intravital microscopy strategies, which can be used to elucidate cellular or molecular interactions in a fluorescent mouse model. We crossbred transgenic TIE2GFP mice with nude BALB/c mice, allowing the breeding of immunocompetent and immunodeficient mouse models expressing green fluorescent protein (GFP) in vascular endothelium. Then, we surgically exposed various tissues of interest to perform intravital microscopy. By utilizing simple tissue preparation procedures and confocal or two-photon microscopy, we produced high-resolution static snapshots, dynamic sequences, and 3D reconstructions of orthotopically grown mammary tumor, skin inflammation, brain, and muscle. The homogenous detection of GFP expressed by endothelial cells and a combination of fluorescence agents enabled landmarking of tumor microenvironment and precise molecular tagging. Simple intravital microscopy procedures on TIE2GFP mice allowed a real-time multi-color visualization of tissue microenvironment, underlining that robust microscopy strategies are relatively simple and can be readily available for many tissues of interest.