Successful adaptation of three-dimensional inversion methodologies for archaeological-scale, total-field magnetic data sets

Three-dimensional inversion plays an important role in the quantitative interpretation of magnetic data in exploration problems, and magnetic amplitude data can be an effective tool in cases in which remanently magnetized materials are present. Because amplitude data are typically calculated from total-field anomaly data, the error levels must be characterized for inversions. Lack of knowledge of the error in amplitude data hinders the ability to properly estimate the data misfit associated with an inverse model and, therefore, the selection of the appropriate regularization parameter for a final model. To overcome these challenges, we have investigated the propagation of errors from total-field anomaly to amplitude data. Using parametric bootstrapping, we find that the standard deviation of the noise in amplitude data is approximately equal to that of the noise in total-field anomaly data when the amplitude data are derived from the conversion of total-field data to three orthogonal components. We then illustrate how the equivalent source method can be used to estimate the error in total-field anomaly data when needed. The obtained noise estimate can be applied to amplitude inversion to recover an optimal inverse model by applying the discrepancy principle. We test this method on synthetic and field data and determine its effectiveness.

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Probing 3-d Electrical Conductivity of the Mantle Using 6 Years of Swarm, Cryosat-2 and Observatory Magnetic Data and Exploiting Matrix Q-responses Approach

10.21203/rs.3.rs-94930/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Alexey Kuvshinov ◽

Alexander Grayver ◽

Lars Toffner-Clausen ◽

Nils Olsen

Keyword(s):

Electrical Conductivity ◽

Spherical Harmonic ◽

Geomagnetic Field ◽

Input Data ◽

Transfer Functions ◽

Three Dimensional ◽

Magnetic Potential ◽

Magnetic Data ◽

Joint Analysis ◽

Data Sets

Abstract This study presents results of mapping three-dimensional (3-D) variations of the electrical conductivity in a depths range from 400 to 1200 km using six years of magnetic data from the Swarm and CryoSat-2 satellites as well as from ground observatories. The approach involves the 3-D inversion of matrix Q-responses (transfer functions) that relate spherical harmonic coefficients of external (inducing) and internal (induced) origin of the magnetic potential. Transfer functions were estimated from geomagnetic field variations at periods ranging from 2 to 40 days. We study the effect of different combinations of input data sets on the transfer functions. We also present a new global 1-D conductivity prole based on a joint analysis of satellite tidal signals and global magnetospheric Q-responses.

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A new method for determination of magnetization direction

Geophysics ◽

10.1190/1.2356116 ◽

2006 ◽

Vol 71 (6) ◽

pp. L69-L73 ◽

Cited By ~ 79

Author(s):

Neal Dannemiller ◽

Yaoguo Li

Keyword(s):

Large Deviation ◽

Three Dimensional ◽

Vertical Gradient ◽

Data Interpretation ◽

Magnetic Data ◽

Data Sets ◽

Magnetization Direction ◽

Total Magnetization ◽

Total Gradient

The characterization and interpretation of magnetic anomalies rely upon knowledge of the total magnetization direction. Magnetization is usually assumed to consist solely, or primarily, of induced magnetization. The presence of strong remanent magnetization can alter the direction significantly and consequently adversely affect the interpretation, leading to erroneous sizes or shapes of causative bodies. Therefore, it is imperative to have some understanding of the total magnetization direction. We propose a method based upon the correlation between two quantities in magnetic data interpretation: the vertical gradient and the total gradient of the reduced-to-pole (RTP) field. This method is tested on both synthetic and field data sets. The results show that the method is effective in a variety of situations, including those with two-dimensional and three-dimensional dipping bodies and a field example that has a large deviation between the inducing field direction and the total magnetization direction.

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Comparison of grid Euler deconvolution with and without 2D constraints using a realistic 3D magnetic basement model

Geophysics ◽

10.1190/1.1925745 ◽

2005 ◽

Vol 70 (3) ◽

pp. L13-L21 ◽

Cited By ~ 21

Author(s):

Simon E. Williams ◽

J. Derek Fairhead ◽

Guy Flanagan

Keyword(s):

Three Dimensional ◽

Euler Method ◽

Magnetic Data ◽

Data Sets ◽

Euler Deconvolution ◽

Data Set ◽

Distinct Source ◽

Magnetic Basement ◽

Modeling Strategy ◽

Source Geometry

We describe the application of a 2D-constrained grid Euler deconvolution method which is able to determine for each solution window whether the source structure is two dimensional, three dimensional, or poorly defined and to estimate the source location and depth. In each solution window, eigenvalues and eigenvectors are derived from the Euler equations and compared to threshold levels. A single eigenvalue below the given threshold and lying in the x–y-plane is shown to indicate a 2D source, while the absence of such an eigenvalue indicates a 3D source geometry. Two small eigenvalues indicate the field in the window has no distinct source. Applying these criteria to each solution window allows us to generate a map of source-geometry distribution. We evaluate the effectiveness of 2D-constrained grid Euler deconvolution using synthetic magnetic data generated from a 3D basement model based on real topography from an area with surface-exposed faulting. This modeling strategy provides a complex, nonidealized data set that compares Euler depth estimates directly to the known basement surface depth. Our results indicate that noninteger structural indices can be the most appropriate choice for some data sets, and the 2D-constrained grid Euler method images magnetic basement structure more clearly and unambiguously than the conventional grid Euler method.

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Probing 3-D electrical conductivity of the mantle using 6 years of Swarm, CryoSat-2 and observatory magnetic data and exploiting matrix Q-responses approach

Earth Planets and Space ◽

10.1186/s40623-020-01341-9 ◽

2021 ◽

Vol 73 (1) ◽

Cited By ~ 2

Author(s):

Alexey Kuvshinov ◽

Alexander Grayver ◽

Lars Tøffner-Clausen ◽

Nils Olsen

Keyword(s):

Electrical Conductivity ◽

Spherical Harmonic ◽

Geomagnetic Field ◽

Input Data ◽

Transfer Functions ◽

Three Dimensional ◽

Magnetic Data ◽

Joint Analysis ◽

Data Sets ◽

Conductivity Profile

AbstractThis study presents results of mapping three-dimensional (3-D) variations of the electrical conductivity in depths ranging from 400 to 1200 km using 6 years of magnetic data from the Swarm and CryoSat-2 satellites as well as from ground observatories. The approach involves the 3-D inversion of matrix Q-responses (transfer functions) that relate spherical harmonic coefficients of external (inducing) and internal (induced) origin of the magnetic potential. Transfer functions were estimated from geomagnetic field variations at periods ranging from 2 to 40 days. We study the effect of different combinations of input data sets on the transfer functions. We also present a new global 1-D conductivity profile based on a joint analysis of satellite tidal signals and global magnetospheric Q-responses.

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Computer-aided methods for 3-D visualization of serial sections and thick biological specimens

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100129930 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1060-1061

Author(s):

Mark Ellisman ◽

Maryann Martone ◽

Gabriel Soto ◽

Eleizer Masliah ◽

David Hessler ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Three Dimensional ◽

Neuritic Plaque ◽

Dimensional Structure ◽

Data Sets ◽

Molecular Physiology ◽

Research Activities ◽

Computer Aided ◽

Dimensional Reconstruction

Structurally-oriented biologists examine cells, tissues, organelles and macromolecules in order to gain insight into cellular and molecular physiology by relating structure to function. The understanding of these structures can be greatly enhanced by the use of techniques for the visualization and quantitative analysis of three-dimensional structure. Three projects from current research activities will be presented in order to illustrate both the present capabilities of computer aided techniques as well as their limitations and future possibilities.The first project concerns the three-dimensional reconstruction of the neuritic plaques found in the brains of patients with Alzheimer's disease. We have developed a software package “Synu” for investigation of 3D data sets which has been used in conjunction with laser confocal light microscopy to study the structure of the neuritic plaque. Tissue sections of autopsy samples from patients with Alzheimer's disease were double-labeled for tau, a cytoskeletal marker for abnormal neurites, and synaptophysin, a marker of presynaptic terminals.

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Elastic transformation of histological slices allows precise co-registration with microCT data sets for a refined virtual histology approach

Scientific Reports ◽

10.1038/s41598-021-89841-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jonas Albers ◽

Angelika Svetlove ◽

Justus Alves ◽

Alexander Kraupner ◽

Francesca di Lillo ◽

...

Keyword(s):

Three Dimensional ◽

High Specificity ◽

Histopathological Analysis ◽

Specific Information ◽

Data Sets ◽

Virtual Histology ◽

Novel Approach ◽

Cell Tissue ◽

Immuno Histochemistry ◽

3D Information

AbstractAlthough X-ray based 3D virtual histology is an emerging tool for the analysis of biological tissue, it falls short in terms of specificity when compared to conventional histology. Thus, the aim was to establish a novel approach that combines 3D information provided by microCT with high specificity that only (immuno-)histochemistry can offer. For this purpose, we developed a software frontend, which utilises an elastic transformation technique to accurately co-register various histological and immunohistochemical stainings with free propagation phase contrast synchrotron radiation microCT. We demonstrate that the precision of the overlay of both imaging modalities is significantly improved by performing our elastic registration workflow, as evidenced by calculation of the displacement index. To illustrate the need for an elastic co-registration approach we examined specimens from a mouse model of breast cancer with injected metal-based nanoparticles. Using the elastic transformation pipeline, we were able to co-localise the nanoparticles to specifically stained cells or tissue structures into their three-dimensional anatomical context. Additionally, we performed a semi-automated tissue structure and cell classification. This workflow provides new insights on histopathological analysis by combining CT specific three-dimensional information with cell/tissue specific information provided by classical histology.

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Validation of Scolioscan Air-Portable Radiation-Free Three-Dimensional Ultrasound Imaging Assessment System for Scoliosis

Sensors ◽

10.3390/s21082858 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2858

Author(s):

Kelly Ka-Lee Lai ◽

Timothy Tin-Yan Lee ◽

Michael Ka-Shing Lee ◽

Joseph Chi-Ho Hui ◽

Yong-Ping Zheng

Keyword(s):

Ultrasound Imaging ◽

Imaging System ◽

Outcome Measurement ◽

Three Dimensional ◽

3D Ultrasound ◽

Mean Difference ◽

Assessment System ◽

Absolute Difference ◽

Data Sets ◽

Low Profile

To diagnose scoliosis, the standing radiograph with Cobb’s method is the gold standard for clinical practice. Recently, three-dimensional (3D) ultrasound imaging, which is radiation-free and inexpensive, has been demonstrated to be reliable for the assessment of scoliosis and validated by several groups. A portable 3D ultrasound system for scoliosis assessment is very much demanded, as it can further extend its potential applications for scoliosis screening, diagnosis, monitoring, treatment outcome measurement, and progress prediction. The aim of this study was to investigate the reliability of a newly developed portable 3D ultrasound imaging system, Scolioscan Air, for scoliosis assessment using coronal images it generated. The system was comprised of a handheld probe and tablet PC linking with a USB cable, and the probe further included a palm-sized ultrasound module together with a low-profile optical spatial sensor. A plastic phantom with three different angle structures built-in was used to evaluate the accuracy of measurement by positioning in 10 different orientations. Then, 19 volunteers with scoliosis (13F and 6M; Age: 13.6 ± 3.2 years) with different severity of scoliosis were assessed. Each subject underwent scanning by a commercially available 3D ultrasound imaging system, Scolioscan, and the portable 3D ultrasound imaging system, with the same posture on the same date. The spinal process angles (SPA) were measured in the coronal images formed by both systems and compared with each other. The angle phantom measurement showed the measured angles well agreed with the designed values, 59.7 ± 2.9 vs. 60 degrees, 40.8 ± 1.9 vs. 40 degrees, and 20.9 ± 2.1 vs. 20 degrees. For the subject tests, results demonstrated that there was a very good agreement between the angles obtained by the two systems, with a strong correlation (R2 = 0.78) for the 29 curves measured. The absolute difference between the two data sets was 2.9 ± 1.8 degrees. In addition, there was a small mean difference of 1.2 degrees, and the differences were symmetrically distributed around the mean difference according to the Bland–Altman test. Scolioscan Air was sufficiently comparable to Scolioscan in scoliosis assessment, overcoming the space limitation of Scolioscan and thus providing wider applications. Further studies involving a larger number of subjects are worthwhile to demonstrate its potential clinical values for the management of scoliosis.

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A Review of Geophysical Modeling Based on Particle Swarm Optimization

Surveys in Geophysics ◽

10.1007/s10712-021-09638-4 ◽

2021 ◽

Author(s):

Francesca Pace ◽

Alessandro Santilano ◽

Alberto Godio

Keyword(s):

Particle Swarm Optimization ◽

Inverse Modeling ◽

Critical Evaluation ◽

Particle Swarm ◽

Geophysical Data ◽

Magnetic Data ◽

Data Sets ◽

Swarm Optimization ◽

Geophysical Modeling ◽

Original Works

AbstractThis paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical fields are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefits and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle different data sets without conflicting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the benefit of PSO practitioners or inexperienced researchers.

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Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation

Journal of Geodesy ◽

10.1007/s00190-019-01325-y ◽

2019 ◽

Vol 93 (12) ◽

pp. 2651-2660 ◽

Cited By ~ 2

Author(s):

Sergey Samsonov

Keyword(s):

Time Series ◽

Surface Deformation ◽

Ground Deformation ◽

Three Dimensional ◽

Data Sets ◽

Ice Flow ◽

The North ◽

Glacier Ice ◽

Deformation Component ◽

3D Deformation

AbstractThe previously presented Multidimensional Small Baseline Subset (MSBAS-2D) technique computes two-dimensional (2D), east and vertical, ground deformation time series from two or more ascending and descending Differential Interferometric Synthetic Aperture Radar (DInSAR) data sets by assuming that the contribution of the north deformation component is negligible. DInSAR data sets can be acquired with different temporal and spatial resolutions, viewing geometries and wavelengths. The MSBAS-2D technique has previously been used for mapping deformation due to mining, urban development, carbon sequestration, permafrost aggradation and pingo growth, and volcanic activities. In the case of glacier ice flow, the north deformation component is often too large to be negligible. Historically, the surface-parallel flow (SPF) constraint was used to compute the static three-dimensional (3D) velocity field at various glaciers. A novel MSBAS-3D technique has been developed for computing 3D deformation time series where the SPF constraint is utilized. This technique is used for mapping 3D deformation at the Barnes Ice Cap, Baffin Island, Nunavut, Canada, during January–March 2015, and the MSBAS-2D and MSBAS-3D solutions are compared. The MSBAS-3D technique can be used for studying glacier ice flow at other glaciers and other surface deformation processes with large north deformation component, such as landslides. The software implementation of MSBAS-3D technique can be downloaded from http://insar.ca/.

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