Accurate Spatial Location Research Articles

Total Variation Constrained Graph Manifold Learning Strategy for Cerenkov Luminescence Tomography.

Harnessing the power and flexibility of radiolabeled molecules, Cerenkov luminescence tomography (CLT) provides a novel technique for non-invasive visualisation and quantification of viable tumour cells in a living organism. However, owing to the photon scattering effect and the ill-posed inverse problem, CLT still suffers from insufficient spatial resolution and shape recovery in various preclinical applications. In this study, we proposed a total variation constrained graph manifold learning (TV-GML) strategy for achieving accurate spatial location, dual-source resolution, and tumour morphology. TV-GML integrates the isotropic total variation term and dynamic graph Laplacian constraint to make a trade-off between edge preservation and piecewise smooth region reconstruction. Meanwhile, the tetrahedral mesh-Cartesian grid pair method based on the k-nearest neighbour, and the adaptive and composite Barzilai-Borwein method, were proposed to ensure global super linear convergence of the solution of TV-GML. The comparison results of both simulation experiments and in vivo experiments further indicated that TV-GML achieved superior reconstruction performance in terms of location accuracy, dual-source resolution, shape recovery capability, robustness, and in vivo practicability. Significance: We believe that this novel method will be beneficial to the application of CLT for quantitative analysis and morphological observation of various preclinical applications and facilitate the development of the theory of solving inverse problem.

Planning-oriented optimization strategy for visualizing power distribution networks: from global to local

ABSTRACT The spatial distribution of power facilities is uneven, thereby making the topology of geographical wiring diagrams (GWDs) based on the actual coordinates unclear. A single-line diagram has the advantage of a clear topology but it lacks spatial locations. A GWD has the advantage of accurate spatial locations but it lacks a clear topology. Visualizing distribution networks for planning requires both features. We proposed a new planning-oriented method for optimizing the visualization of distribution networks. From the global perspective, we proposed an improved force-directed (FD) algorithm by introducing a space restriction strategy and node–edge repulsion strategy to promote the expansion of the distance between distribution facilities within a limited buffer. We then constructed the constrained Delaunay triangulation to identify the compact districts (CDs) and used a genetic algorithm to optimize the parameters for the improved FD algorithm. A novel visualization evaluation indicator was also proposed for quantitatively assessing the visualizations. From a local perspective, the fisheye algorithm was used to optimize the CDs to further improve the visualization of the distribution network. We verified the proposed methods with real-world data. We used limited spatial displacement in exchange for maximum topology clarity to balance the accurate spatial location and topology clarity.

Direct depth-domain Bayesian amplitude-variation-with-offset inversion

We have developed a new approach to perform Bayesian linearized amplitude-variation-with-offset (AVO) inversion in the depth domain using nonstationary wavelets. Bayesian linearized AVO inversion, a hybrid approach combining physics-based models with statistical learning, has gained immense popularity because of its superior computational speed and ability to estimate uncertainties in inverted model parameters. Bayesian linearized AVO inversion is performed on time-domain seismic data; therefore, depth-imaged seismic cannot be inverted directly using this method and would require depth-to-time conversion before AVO inversion can be done. Subsequently, time-to-depth conversion of the inverted volumes would be required for reservoir modeling and well placement. Domain conversions introduce additional uncertainty in geophysical workflows. In conventional AVO inversion, the seismic wavelet is assumed to be stationary, and this assumption leads to a restriction in the length of the time window over which the inversion can be performed. Therefore, AVO inversion is usually restricted to a narrow time window around the target of interest, and if multiple targets are present at different depths, multiple inversions must be run on the same volume. Depth-domain amplitude inversion is a recent development and has been previously presented in an iterative formulation. Implementing linearized Bayesian inversion directly in the depth domain using nonstationary wavelets is a convenient new approach that takes advantage of superior computational speed and uncertainty quantification without compromising the accurate spatial location that depth imaging provides. Combining these two ideas creates a novel, unique, and powerful seismic inversion technique that can be useful for quantitative interpretation and reservoir characterization.

A light field measurement system through PSF estimation by a morphology-based method

Light field imaging technology can obtain three-dimensional (3D) information of a test surface in a single exposure. Traditional light field reconstruction algorithms not only take a long time to trace back to the original image, but also require the exact parameters of the light field system, such as the position and posture of a microlens array (MLA), which will cause errors in the reconstructed image if these parameters cannot be precisely obtained. This paper proposes a reconstruction algorithm for light field imaging based on the point spread function (PSF), which does not require prior knowledge of the system. The accurate PSF derivation process of a light field system is presented, and modeling and simulation were conducted to obtain the relationship between the spatial distribution characteristics and the PSF of the light field system. A morphology-based method is proposed to analyze the overlapping area of the subimages of light field images to identify the accurate spatial location of the MLA used in the system, which is thereafter used to accurately refocus light field imaging. A light field system is built to verify the algorithm’s effectiveness. Experimental results show that the measurement accuracy is increased over 41.0% compared with the traditional method by measuring a step standard. The accuracy of parameters is also improved through a microstructure measurement with a peak-to-valley value of 25.4% and root mean square value of 23.5% improvement. This further validates that the algorithm can effectively improve the refocusing efficiency and the accuracy of the light field imaging results with the superiority of refocusing light field imaging without prior knowledge of the system. The proposed method provides a new solution for fast and accurate 3D measurement based on a light field.

Weighted Geocoding Method Based on Chinese Word Segmentation and Its Application to Spatial Positioning of COVID-19 Epidemic Prevention and Control

Locating the coronavirus disease 2019 (COVID-19)cases in the accurate place is important in epidemic prevention and control. Geocoding is an effective method to achieve information space positioning with address description. The English based geocoding methodology is not suitable for Chinese address. Composition and positioning methods of Chinese address are discussed. According to the characteristics of high complexity and diversity of Chinese address, a Chinese word segmentation weighted address matching algorithm considering a variety of semantics is designed, including the same pronunciation but different Chinese word address, abbreviation and alias of Chinese address, different description of the same address. And the matching accuracy and efficiency of the algorithm are tested by using the COVID-19 cases' addresses in Wuhan. The result indicates the algorithm is efficient, accurate, and intelligent, which can realize the efficient location of the COVID-19 cases address, and provide accurate spatial location information for epidemic prevention and control by quickly positioning of the COVID-19 cases.

Super-Resolution Mapping of Impervious Surfaces from Remotely Sensed Imagery with Points-of-Interest

The accurate mapping of impervious surfaces is of key significance for various urban applications. Usually, traditional methods extract the proportion image of impervious surfaces from remote sensing images; however, the proportion image cannot specify where the impervious surfaces spatially distribute within a pixel. Meanwhile, impervious surfaces often locate urban areas and have a strong correlation with the relatively new big (geo)data points of interest (POIs). This study, therefore, proposed a novel impervious surfaces mapping method (super-resolution mapping of impervious surfaces, SRMIS) by combining a super-resolution mapping technique and POIs to increase the spatial resolution of impervious surfaces in proportion images and determine the accurate spatial location of impervious surfaces within each pixel. SRMIS was evaluated using a 10-m Sentinel-2 image and a 30-m Landsat 8 Operational Land Imager (OLI) image of Nanjing city, China. The experimental results show that SRMIS generated satisfactory impervious surface maps with better-classified image quality and greater accuracy than a traditional hard classifier, the two existing super-resolution mapping (SRM) methods of the subpixel-swapping algorithm, or the method using both pixel-level and subpixel-level spatial dependence. The experimental results show that the overall accuracy increase of SRMIS was from 2.34% to 5.59% compared with the hard classification method and the two SRM methods in the first experiment, while the overall accuracy of SRMIS was 1.34–3.09% greater than that of the compared methods in the second experiment. Hence, this study provides a useful solution to combining SRM techniques and the relatively new big (geo)data (i.e., POIs) to extract impervious surface maps with a higher spatial resolution than that of the input remote sensing images, and thereby supports urban research.

Awakening the BALROG: BAyesian Location Reconstruction Of GRBs

The accurate spatial location of gamma-ray bursts (GRBs) is crucial for both accurately characterizing their spectra and follow-up observations by other instruments. The Fermi Gamma-ray Burst Monit ...

Three-dimensional laparoscopic surgery: a revolutionary technique or a transitional technique

Three-dimensional (3D) laparoscopic surgery has been developed rapidly in China since 2012. Based on mature two-dimensional (2D) laparoscopic surgery, 3D laparoscopic surgery has the same technique as 2D, with similar indication as 2D as well. However, 3D laparoscopic surgery can offer better depth description, more accurate spatial location, and less error in operation. It might offer better visional experience if hybrid with virtual reality or with 4K in the future. But in current status, laparoscopy with 3D technique is only a technique with innovation, but not a revolutionary technique. Key words: Gastrointestinal neoplasms; Surgical procedures, operative; Laparoscopy; Tree-dimensional technique

Real-time bioluminescence and tomographic imaging of gastric cancer in a novel orthotopic mouse model

Gastric cancer is the second leading cause of cancer mortality worldwide. Understanding the multistep process of carcinogenesis of gastric cancer is pivotal to develop novel therapeutic strategies. Molecular imaging in preclinical cancer models bridges the gap of laboratory-based experiment and clinical translation. To this end, the human gastric cancer cell line SGC-7901 was established to stably express luciferase and GFP by lentiviral transduction (SGC7901-Luc-GFP). Preclinical models were developed by orthotopic transplantation of SGC-7901-Luc-GFP into the sub-serosal layer of the stomach of immunocompromised mice. Tumor progression and therapeutic responses were dynamically tracked by bioluminescence imaging (BLI). Bioluminescence tomography (BLT) was used to monitor stereoscopic morphological and signal changes during tumor progression. Good correlation between cell number and bio-luminescence/fluorescence intensity was observed (R(2)=0.9983/r(2)=0.9974) in vitro. Tumor progression and therapeutic response could be successfully followed directly by BLI. Importantly, BLT provided a more accurate spatial location and tomographic quantification of the internal lesion. In conclusion, our novel bioluminescence-based preclinical gastric cancer models enable superior, noninvasive monitoring gastric cancer progression and their drug responses. The BLT technique in particular, may have great potential for future oncological studies.

Prediction of joint center location by customizable multiple regressions: Application to clavicle, scapula and humerus

Accurate spatial location of joint center (JC) is a key issue in motion analysis since JC locations are used to define standardized anatomical frames, in which results are represented. Accurate and reproducible JC location is important for data comparison and data exchange. This paper presents a method for JC locations based on the multiple regression algorithms without preliminary assumption on the behavior of the joint-of-interest. Regression equations were obtained from manually palpable ALs on each bone-of-interest. Results are presented for all joint surfaces found on the clavicle, scapula and humeral bone. Mean accuracy errors on the JC locations obtained on dry bones were 5.2±2.5 mm for the humeral head, 2.5±1.1 mm for the humeral trochlea, 2.3±0.9 mm for the humeral capitulum, 8.2±3.9 mm for the scapula glenoid cavity, 7.2±3.2 mm for the scapular aspect of the acromio-clavicular joint, 3.5±1.8 mm for the clavicular aspect of the sternoclavicular joint and 3.2±1.4 mm for the clavicular aspect of the acromio-clavicular joint. In-vitro and in-vivo validation accuracy was 5.3 and 8.5 mm, respectively, for the humeral head center location. Regression coefficients for joint radius dimension and joint surface orientation were also processed and reported in this paper.

The use of computerized navigation in the treatment of gunshot and shrapnel injury

Objective: Trauma surgeons encounter numerous penetrating injuries nowadays. In some cases, missiles causing infection, pain and discomfort, or those retained within joints, bursae and other strategic sites, must be removed. This paper describes an innovative high-tech modality for use in the immediate removal of shrapnel and bullets from strategic anatomical sites.Methods: Surgical computerized navigation based on real-time acquisition of fluoroscopic data was employed. Several fluoroscopic images of the required anatomical site were obtained. The accurate spatial location of the foreign object could be seen on the images displayed on the computer screen. No further fluoroscopic radiation was necessary. During surgery, the infra-red camera tracked the position of a surgical probe on the patient's anatomy and continuously updated its three-dimensional position simultaneously on all displayed images until the missile's location was reached.Results: The use of percutaneous fluoroscopic navigation to remove retained metal objects, including bullets and shrapnel, has proved itself in 12 cases as an accurate measure involving reduced exposure to radiation. In contrast to CT- or MRI-based navigation, computerized fluoroscopic navigation does not require long preliminary preparation. Thus, it is highly efficient in the treatment of acute trauma victims.Conclusions: The use of this accurate technique in complex and dangerous situations where the foreign body is located in proximity to blood vessels, nerves and narrow ‘safe-zones’, is promising. This innovative technique reduces surgical time and radiation exposure. In our experience, it has rendered percutaneous missile removal much safer, even in hazardous situations.

Tracking Changes in Oil Exploration and Development Technology and Their Economic Implications

The objectives of this paper are to identify improvements made during the past 15 years in the technology and methods used for the exploration, development, and production of oil reserves in the U.S. Wherever possible, observations have been made with respect to the effect of these improvements on the exploitation of these reserves. Areas of research that will be of interest in the future have also been referenced. In this regard, it may be recognized that after an era in which it was important to find oil at any price to ensure supplies, the petroleum industry is now entering a period of systematic research to reduce costs in response to the new market conditions.